In this videos we are going to discuss about the complete road map to be a expert in python programming. Python has been the most versatile programming language through which you can select any path such as web development, machine learning ,data scientist, data analyst

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Python AI Tech news : https://www.youtube.com/playlist?list=PLTDARY42LDV6iFI3Dd3oNf6oIvuJs_EKX

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►Data Science Projects: 
https://www.youtube.com/watch?v=S_F_c9e2bz4&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&pp=iAQB

►Learn In One Tutorials

Statistics in 6 hours: https://www.youtube.com/watch?v=LZzq1zSL1bs&t=9522s&pp=ygUVa3Jpc2ggbmFpayBzdGF0aXN0aWNz

Machine Learning In 6 Hours: https://www.youtube.com/watch?v=JxgmHe2NyeY&t=4733s&pp=ygUba3Jpc2ggbmFpayBtYWNoaW5lIGxlYXJuaW5n

Deep Learning 5 hours : https://www.youtube.com/watch?v=d2kxUVwWWwU&t=1210s&pp=ygUYa3Jpc2ggbmFpayBkZWVwIGxlYXJuaW5n


►Learn In a Week Playlist

Statistics:https://www.youtube.com/watch?v=11unm2hmvOQ&list=PLZoTAELRMXVMgtxAboeAx-D9qbnY94Yay

Machine Learning : https://www.youtube.com/watch?v=z8sxaUw_f-M&list=PLZoTAELRMXVPjaAzURB77Kz0YXxj65tYz

Deep Learning:https://www.youtube.com/watch?v=8arGWdq_KL0&list=PLZoTAELRMXVPiyueAqA_eQnsycC_DSBns

NLP : https://www.youtube.com/watch?v=w3coRFpyddQ&list=PLZoTAELRMXVNNrHSKv36Lr3_156yCo6Nn

►Detailed Playlist:

Stats For Data Science In Hindi : https://www.youtube.com/watch?v=7y3XckjaVOw&list=PLTDARY42LDV6YHSRo669_uDDGmUEmQnDJ&pp=gAQB

Machine Learning In English : https://www.youtube.com/watch?v=bPrmA1SEN2k&list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe

Machine Learning In Hindi : https://www.youtube.com/watch?v=7uwa9aPbBRU&list=PLTDARY42LDV7WGmlzZtY-w9pemyPrKNUZ&pp=gAQB

Complete Deep Learning: https://www.youtube.com/watch?v=YFNKnUhm_-s&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi

Complete Road Map To Be Expert In Python- Follow My Way

In this video I will how you the complete roadmap to follow to prepare machine learning with all videos and materials  
Register now for the upcoming DLCVNLP course in collaboration with Ineuron
Mentors: Krish And Sudhanhu
Register now:-
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All the details are given in the above link
All Playlist In My channel
Complete ML Playlist :https://www.youtube.com/playlist?list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe
Complete NLP Playlist:https://www.youtube.com/playlist?list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm
Docker End To End Implementation: https://www.youtube.com/playlist?list=PLZoTAELRMXVNKtpy0U_Mx9N26w8n0hIbs
Live stream Playlist: https://www.youtube.com/playlist?list=PLZoTAELRMXVNxYFq_9MuiUdn2YnlFqmMK
Machine Learning Pipelines: https://www.youtube.com/playlist?list=PLZoTAELRMXVNKtpy0U_Mx9N26w8n0hIbs
Pytorch Playlist: https://www.youtube.com/playlist?list=PLZoTAELRMXVNxYFq_9MuiUdn2YnlFqmMK
Feature Engineering  :https://www.youtube.com/playlist?list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN
Live Projects        :https://www.youtube.com/playlist?list=PLZoTAELRMXVOFnfSwkB_uyr4FT-327noK
Kaggle competition   :https://www.youtube.com/playlist?list=PLZoTAELRMXVPiKOxbwaniXjHJ02bdkLWy
Mongodb with Python  :https://www.youtube.com/playlist?list=PLZoTAELRMXVN_8zzsevm1bm6G-plsiO1I
MySQL With Python    :https://www.youtube.com/playlist?list=PLZoTAELRMXVMd3RF7p-u7ezEysGaG9JmO
Deployment Architectures:https://www.youtube.com/playlist?list=PLZoTAELRMXVOPzVJiSJAn9Ly27Fi1-8ac
Amazon sagemaker     :https://www.youtube.com/playlist?list=PLZoTAELRMXVONh5mHrXowH6-dgyWoC_Ew

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#machinelearning
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Complete Roadmap To Follow To  Prepare Machine Learning With All Videos And Materials

Hello All,
Welcome to the Python Crash Course. In this video we will see about python basics datatypes and operation

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Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning!

Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Tutorial 1- Anaconda Installation and Python Basics

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You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning!

Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=sr_1_1?keywords=krish+naik&qid=1560943725&s=gateway&sr=8-1

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Why Python is the Best Programming Language For Machine Learning?

Hello All,
Welcome to the Python Crash Course. In this video we will see about python List and Boolean Variables

github url : https://github.com/krishnaik06/Machine-Learning-in-90-days

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Buy the Best book of Machine Learning, Deep Learning with python sklearn and tensorflow from below
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You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning!

Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=sr_1_1?keywords=krish+naik&qid=1560943725&s=gateway&sr=8-1

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Tutorial 2 - Python List  and Boolean Variables

Tutorial 3- Python Sets, Dictionaries and Tuples

Hello All,
Welcome to the Python Crash Course. In this video we will see about numpy library

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Buy the Best book of Machine Learning, Deep Learning with python sklearn and tensorflow from below
amazon url:
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You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning!

Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=sr_1_1?keywords=krish+naik&qid=1560943725&s=gateway&sr=8-1

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Tutorial 4 - Numpy and Inbuilt Functions Tutorial

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Welcome to the Python Crash Course. In this video we will understand about Pandas library, Dataframes and Data Series

github url : https://github.com/krishnaik06/Machine-Learning-in-90-days

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Buy the Best book of Machine Learning, Deep Learning with python sklearn and tensorflow from below
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You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning!

Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=sr_1_1?keywords=krish+naik&qid=1560943725&s=gateway&sr=8-1

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Tutorial 5- Pandas, Data Frame and Data Series Part-1

Hello All,
Welcome to the Python Crash Course. In this video we will understand about Pandas library, how to read CSV files and play with different parameters

github url : https://github.com/krishnaik06/Machine-Learning-in-90-days

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Buy the Best book of Machine Learning, Deep Learning with python sklearn and tensorflow from below
amazon url:
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You can buy my book on Finance with Machine Learning and Deep Learning from the below url

amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=as_sl_pc_qf_sp_asin_til?tag=krishnaik06-21&linkCode=w00&linkId=ac229c9a45954acc19c1b2fa2ca96e23&creativeASIN=1789346371

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Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning!

Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=sr_1_1?keywords=krish+naik&qid=1560943725&s=gateway&sr=8-1

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Tutorial 6- Pandas,Reading CSV files With Various Parameters- Part 2

Hello All,
Welcome to the Python Crash Course. In this video we will understand about Pandas library, how to read JSON ,HTML, PICKLE and Eexcel files.

github url : https://github.com/krishnaik06/Machine-Learning-in-90-days

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Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

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Tutorial 7- Pandas-Reading JSON,Reading HTML, Read PICKLE, Read EXCEL Files- Part 3

Hello All,
Welcome to the Python Crash Course. In this video we will understand about as a simple visualization library called as matplotlib library

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NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

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Tutorial 8- Matplotlib (Simple Visualization Library)

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Welcome to the Python Crash Course. In this video we will understand about Seaborn

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Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Tutorial 9- Seaborn Tutorial- Distplot, Joinplot, Pairplot  Part 1

Tutorial 10- Seaborn- Countplot(), Violinplot(), Boxplot()- Part2

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NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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How To Become Expertise in Exploratory Data Analysis

Here is the detailed explanation of Exploratory Data Analysis of the Titanic. Finally we are applying Logistic Regression for the prediction of the survived column.

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References from : Jose Portila EDA Materials And Kaggle

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Tutorial 11-Exploratory Data Analysis(EDA) of Titanic dataset

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Welcome to the Python Crash Course. In this video we will discuss about Functions  in python and positional and keyword arguments

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You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Tutorial 12- Python Functions, Positional and Keywords Arguments

Tutorial 15- Map Functions using Python

Tutorial 13- Python Lambda Functions

Tutorial 16- Filter Functions In Python

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In this we will understand how we can implement the Python Lambda Function

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You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Tutorial 17- Python List Comprehension

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You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

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Tutorial 18- Python Advanced String Formatting

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NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

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Tutorial 19-  Python Iterables vs Iterators

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Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

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Tutorial 20- How To Import All Important Python Data Science Libraries Using Pyforest

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Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi
Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw

NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm

Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk

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Tutorial 21- Python OOPS Tutorial- Classes, Variables, Methods and Objects

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Starter In  Data Science

1  Complete Machine Learning Playlist:(Top 24 videos)

https://www.youtube.com/playlist?list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe

2  Statistics in Machine Learning:(Understand some Concepts With Respect To Data)- Complete Playlist
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3. Feature Engineering(Complete Playlist)
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4. Continue The Complete Machine Learning Playlist(24-all the videos)

5. Live Stream Playlist:(Top 10 videos)
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6. Machine Learning Pipelines

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7. Complete Deep Learning Playlist:
Tensorflow And Keras-https://www.youtube.com/playlist?list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi

Pytorch: https://www.youtube.com/playlist?list=PLZoTAELRMXVNxYFq_9MuiUdn2YnlFqmMK

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12. Machine Learning Interviews: https://www.youtube.com/playlist?list=PLZoTAELRMXVM0zN0cgJrfT6TK2ypCpQdY

Advanced Python- Exception Handling Detailed Explanation In Python

Advanced Python Series- Custom Exception Handling In Python

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Starter In  Data Science

1  Complete Machine Learning Playlist:(Top 24 videos)

https://www.youtube.com/playlist?list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe

2  Statistics in Machine Learning:(Understand some Concepts With Respect To Data)- Complete Playlist
https://www.youtube.com/playlist?list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

3. Feature Engineering(Complete Playlist)
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4. Continue The Complete Machine Learning Playlist(24-all the videos)

5. Live Stream Playlist:(Top 10 videos)
https://www.youtube.com/playlist?list=PLZoTAELRMXVPUyxuK8AphGMuIJHTyuWna

6. Machine Learning Pipelines

https://www.youtube.com/playlist?list=PLZoTAELRMXVMcRQwR5_J8k9S7cffVFq_U

7. Complete Deep Learning Playlist:
Tensorflow And Keras-https://www.youtube.com/playlist?list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi

Pytorch: https://www.youtube.com/playlist?list=PLZoTAELRMXVNxYFq_9MuiUdn2YnlFqmMK

8.  Live Projects Playlist:
https://www.youtube.com/playlist?list=PLZoTAELRMXVOFnfSwkB_uyr4FT-327noK
9. Live stream Playlist: https://www.youtube.com/playlist?list=PLZoTAELRMXVPUyxuK8AphGMuIJHTyuWna
10.Docker Playlist: https://www.youtube.com/playlist?list=PLZoTAELRMXVNKtpy0U_Mx9N26w8n0hIbs
11. Mongodb: https://www.youtube.com/playlist?list=PLZoTAELRMXVN_8zzsevm1bm6G-plsiO1I
12. Machine Learning Interviews: https://www.youtube.com/playlist?list=PLZoTAELRMXVM0zN0cgJrfT6TK2ypCpQdY

Advance Python Series- Public Private And Protected Access Modifiers

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Starter In  Data Science

1  Complete Machine Learning Playlist:(Top 24 videos)

https://www.youtube.com/playlist?list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe

2  Statistics in Machine Learning:(Understand some Concepts With Respect To Data)- Complete Playlist
https://www.youtube.com/playlist?list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO

3. Feature Engineering(Complete Playlist)
https://www.youtube.com/playlist?list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN

4. Continue The Complete Machine Learning Playlist(24-all the videos)

5. Live Stream Playlist:(Top 10 videos)
https://www.youtube.com/playlist?list=PLZoTAELRMXVPUyxuK8AphGMuIJHTyuWna

6. Machine Learning Pipelines

https://www.youtube.com/playlist?list=PLZoTAELRMXVMcRQwR5_J8k9S7cffVFq_U

7. Complete Deep Learning Playlist:
Tensorflow And Keras-https://www.youtube.com/playlist?list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi

Pytorch: https://www.youtube.com/playlist?list=PLZoTAELRMXVNxYFq_9MuiUdn2YnlFqmMK

8.  Live Projects Playlist:
https://www.youtube.com/playlist?list=PLZoTAELRMXVOFnfSwkB_uyr4FT-327noK
9. Live stream Playlist: https://www.youtube.com/playlist?list=PLZoTAELRMXVPUyxuK8AphGMuIJHTyuWna
10.Docker Playlist: https://www.youtube.com/playlist?list=PLZoTAELRMXVNKtpy0U_Mx9N26w8n0hIbs
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12. Machine Learning Interviews: https://www.youtube.com/playlist?list=PLZoTAELRMXVM0zN0cgJrfT6TK2ypCpQdY

Advance Python Series- Inheritance In Python

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Tutorial 22-Univariate, Bivariate and Multivariate Analysis- Part1 (EDA)-Data Science

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Tutorial 23-Univariate, Bivariate and Multivariate Analysis- Part2 (EDA)-Data Science

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Tutorial 24- Histogram in EDA- Data Science

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Tutorial 24-Z Score Statistics Data Science

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Tutorial 25- Probability Density function and CDF- EDA-Data Science

Tutorial 26- Linear Regression Indepth Maths Intuition- Data Science

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#Regularization
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Tutorial 27- Ridge and Lasso Regression Indepth Intuition- Data Science

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Tutorial 28- Ridge and Lasso Regression using Python and Sklearn

Multiple linear regression is the most common form of linear regression analysis. As a predictive analysis, the multiple linear regression is used to explain the relationship between one continuous dependent variable and two or more independent variables.

References - Kirell Ermenko Projects On Linear Regression. This video is dedicated to him

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Multiple Linear Regression using python and sklearn

In regression, "multicollinearity" refers to predictors that are correlated with other predictors. Multicollinearity occurs when your model includes multiple factors that are correlated not just to your response variable, but also to each other. In other words, it results when you have factors that are a bit redundant
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Tutorial 28-MultiCollinearity In Linear Regression- Part 2

In statistics and machine learning, the bias–variance tradeoff is the property of a set of predictive models whereby models with a lower bias in parameter estimation have a higher variance of the parameter estimates across samples, and vice versa
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Machine Learning-Bias And Variance In Depth Intuition| Overfitting Underfitting

The adjusted R-squared is a modified version of R-squared that has been adjusted for the number of predictors in the model. The adjusted R-squared increases only if the new term improves the model more than would be expected by chance. It decreases when a predictor improves the model by less than expected by chance

#RsquareAdjustedRsquare

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Tutorial 29-R square and Adjusted R square Clearly Explained| Machine Learning

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Tutorial 31- Hypothesis Test, Type 1 Error, Type 2 Error

In statistics, the p-value is the probability of obtaining results at least as extreme as the observed results of a statistical hypothesis test, assuming that the null hypothesis is correct
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What Is P Value In Statistics In Simple Language?

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Tutorial 32- All About P Value,T test,Chi Square Test, Anova Test  and When  to Use What?

Most awaited Video. Here is a video which provides a detailed explanation about how you can implement P value,t test and Correlation

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Tutorial 33- P Value,T test, Correlation Implementation with Python- Hypothesis Testing

Most awaited Video. Here is a video which provides a detailed explanation about how you can implement Chi Square Test

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Tutorial 33- Chi Square Test Implementation with Python- Hypothesis Testing- Part 2

Tutorial 34- Performance Metrics For Classification Problem In Machine Learning- Part1

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Tutorial 35- Logistic Regression Indepth Intuition- Part 1| Data Science

Tutorial 36- Logistic Regression Indepth Intuition- Part 2| Data Science

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Tutorial 36- Logistic Regression Mutliclass Classification(OneVsRest)- Part 3| Data Science

Entropy gives measure of impurity in a node. In a decision tree building process, two important decisions are to be made — what is the best split(s) and which is the best variable to split a node.

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Tutorial 37: Entropy In Decision Tree Intuition

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Tutorial 38- Decision Tree Information Gain

Tutorial 39- Gini Impurity Intuition In Depth In Decision Tree

Tutorial 40- Decision Tree Split For Numerical Feature

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Advance House Price Prediction- Exploratory Data Analysis- Part 1

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Advance House Price Prediction-Feature Engineering Part 1

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Advance House Price Prediction-Feature Engineering Part 2

Advance House Price Prediction-Feature Selection

Tutorial 41-Performance Metrics(ROC,AUC Curve) For Classification Problem In Machine Learning Part 2

Performance Metrics On MultiClass Classification Problems

In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression. k-NN is a type of instance-based learning, or lazy learning, where the function is only approximated locally and all computation is deferred until classification.

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K Nearest Neighbor classification with Intuition and practical solution

In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression.[1] In both cases, the input consists of the k closest training examples in the feature space. The output depends on whether k-NN is used for classification or regression:

In k-NN classification, the output is a class membership. An object is classified by a plurality vote of its neighbors, with the object being assigned to the class most common among its k nearest neighbors (k is a positive integer, typically small). If k = 1, then the object is simply assigned to the class of that single nearest neighbor.
In k-NN regression, the output is the property value for the object. This value is the average of the values of k nearest neighbors.
k-NN is a type of instance-based learning, or lazy learning, where the function is only approximated locally and all computation is deferred until classification. The k-NN algorithm is among the simplest of all machine learning algorithms.

Both for classification and regression, a useful technique can be used to assign weight to the contributions of the neighbors, so that the nearer neighbors contribute more to the average than the more distant ones. For example, a common weighting scheme consists in giving each neighbor a weight of 1/d, where d is the distance to the neighbor.

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K Nearest Neighbour Easily Explained with Implementation

Bootstrap aggregating, also called bagging, is a machine learning ensemble meta-algorithm designed to improve the stability and accuracy of machine learning algorithms used in statistical classification and regression


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Tutorial 42 - Ensemble: What is Bagging (Bootstrap Aggregation)?

Hello All,
In this video we will be discussing about the Random Forest Classifier and Regressor which is basically a Bagging Technique

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Tutorial 43-Random Forest Classifier and Regressor

Machine Learning algorithms tend to produce unsatisfactory classifiers when faced with imbalanced datasets. For any imbalanced data set, if the event to be predicted belongs to the minority class and the event rate is less than 5%, it is usually referred to as a rare even

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Tutorial 45-Handling imbalanced Dataset  using python- Part 1

Tutorial 46-Handling imbalanced Dataset using python- Part 2

In machine learning, hyperparameter optimization or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process. By contrast, the values of other parameters (typically node weights) are learned.

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Hyperparameter Optimization for Xgboost

In this Video we will discussing about the ADABOOST algorithm which is basically a boosting technique.

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What is AdaBoost (BOOSTING TECHNIQUES)

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Visibility Climate Prediction- You Can Add This In Your Resume

Hello All here is a video which provides the detailed explanation of Euclidean and Manhattan Distance

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Euclidean Distance and Manhattan Distance

Here is a complete intuition behind K Means Clustering Algorithm. We will understand the complete the complete geometric intuition.

K Means Clustering Practical : https://www.youtube.com/watch?v=tAY6jtFoNEA

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K Means Clustering Intuition

Here is a detailed discussion where we understand the intuition behind Hierarchical Clustering.

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Hierarchical Clustering intuition

Density-based spatial clustering of applications with noise (DBSCAN) is a well-known data clustering algorithm that is commonly used in data mining and machine learning.

Based on a set of points (let’s think in a bidimensional space as exemplified in the figure), DBSCAN groups together points that are close to each other based on a distance measurement (usually Euclidean distance) and a minimum number of points. It also marks as outliers the points that are in low-density regions.

#DBSCANclustering

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DBSCAN Clustering Easily Explained with Implementation

Reference Link: https://en.wikipedia.org/wiki/Silhouette_(clustering)#:~:text=The%20silhouette%20value%20is%20a,poorly%20matched%20to%20neighboring%20clusters.

https://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html#sphx-glr-auto-examples-cluster-plot-kmeans-silhouette-analysis-py
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Silhouette (clustering)- Validating Clustering Models- Unsupervised Machine Learning

The curse of dimensionality refers to various phenomena that arise when analyzing and organizing data in high-dimensional spaces that do not occur in low-dimensional settings such as the three-dimensional physical space of everyday experience.

#CurseofDimensionality

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Curse of Dimensionality Easily explained| Machine Learning

Here is a detailed explanation of the Dimesnioanlity Reduction using Principal Component Analysis. 

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Dimensional Reduction| Principal Component Analysis

Here is a detailed explanation of PCA technique which is used for dimesnionality reduction using sklearn and python

Reference :Special thanks to Jose Portila

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Principle Component Analysis (PCA) using sklearn and python

In this video we will be discussing about what is cross validation and what are its different types

1. Leave  P out cross validation
2. K fold Cross Validation
3. Stratified K fold Cross Validation
4. Time Series Cross Validation
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What is Cross Validation and its types?

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Tutorial 42-How To Find Optimal Threshold For Binary Classification - Data Science

In probability theory and statistics, Bayes' theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event
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Tutorial 47- Bayes' Theorem| Conditional Probability- Machine Learning

Guys there were some issue in the previous video. So I have reuploaded it. Sorry for the trouble.

In probability theory and statistics, Bayes' theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event
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Tutorial 48- Naive Bayes' Classifier Indepth Intuition-  Machine Learning

The Naive Bayes classifier is a simple classifier that classifies based on probabilities of events. It is the applied commonly to text classification. Though it is a simple algorithm, it performs well in many text classification problems. Other Pros include less training time and less training data.

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Tutorial 49- How To Apply Naive Bayes' Classifier On Text Data (NLP)- Machine Learning

In machine learning, support-vector machines are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.
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Support Vector Machine (SVM) Basic Intuition- Part 1| Machine Learning

Maths Intuition Behind Support Vector Machine Part 2 | Machine Learning Data Science

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SVM Kernels In-depth Intuition- Polynomial Kernels Part 3 | Machine Learning Data Science

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Part2 : https://www.youtube.com/watch?v=Js3GLb1xPhc
⭐ Kite is a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I've been using Kite for a few months and I love it! https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=krishnaik&utm_content=description-only
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Feature Engineering  :https://www.youtube.com/playlist?list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN
Live Projects        :https://www.youtube.com/playlist?list=PLZoTAELRMXVOFnfSwkB_uyr4FT-327noK
Kaggle competition   :https://www.youtube.com/playlist?list=PLZoTAELRMXVPiKOxbwaniXjHJ02bdkLWy
Mongodb with Python  :https://www.youtube.com/playlist?list=PLZoTAELRMXVN_8zzsevm1bm6G-plsiO1I
MySQL With Python    :https://www.youtube.com/playlist?list=PLZoTAELRMXVMd3RF7p-u7ezEysGaG9JmO
Deployment Architectures:https://www.youtube.com/playlist?list=PLZoTAELRMXVOPzVJiSJAn9Ly27Fi1-8ac
Amazon sagemaker     :https://www.youtube.com/playlist?list=PLZoTAELRMXVONh5mHrXowH6-dgyWoC_Ew


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SVM Kernal- Polynomial And RBF Implementation Using Sklearn- Machine Learning

Gradient boosting is typically used with decision trees (especially CART trees) of a fixed size as base learners. For this special case, Friedman proposes a modification to gradient boosting method which improves the quality of fit of each base learner.

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Gradient Boosting In Depth Intuition- Part 1 Machine Learning

Gradient boosting is typically used with decision trees (especially CART trees) of a fixed size as base learners. For this special case, Friedman proposes a modification to gradient boosting method which improves the quality of fit of each base learner.
wiki link :https://en.wikipedia.org/wiki/Gradient_boosting

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Gradient Boosting Complete Maths Indepth Intuiton Explained| Machine Learning- Part2

XGBoost is a decision-tree-based ensemble Machine Learning algorithm that uses a gradient boosting framework. In prediction problems involving unstructured data (images, text, etc.) artificial neural networks tend to outperform all other algorithms or frameworks.
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#xgboostclassifier
#xgboost

Xgboost Classification Indepth Maths Intuition- Machine Learning Algorithms🔥🔥🔥🔥

XGBoost is a decision-tree-based ensemble Machine Learning algorithm that uses a gradient boosting framework. In prediction problems involving unstructured data (images, text, etc.) artificial neural networks tend to outperform all other algorithms or frameworks.
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MySQL With Python    :https://www.youtube.com/playlist?list=PLZoTAELRMXVMd3RF7p-u7ezEysGaG9JmO
Deployment Architectures:https://www.youtube.com/playlist?list=PLZoTAELRMXVOPzVJiSJAn9Ly27Fi1-8ac
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#xgboost

Xgboost Regression In-Depth Intuition Explained- Machine Learning Algorithms 🔥🔥🔥🔥

github: https://github.com/krishnaik06/Live-Co---vid-Tracker
In this video we will be developing an application for tracking Co--vid cases uing python. We will also be performing lot of Exploratory data analysis to understand more about the data.
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Data Science In Medical-Live Tracking Of CO--VID Cases In India using Python

github link: https://github.com/krishnaik06/EDA_Sweetviz

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Perform EDA In Seconds With Visualization Using SweetViz Library

All thanks To Anuj Vyas  for sharing the work to everyone.
Linked Id : https://www.linkedin.com/in/anujkvyas/
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Docker Playlist: https://www.youtube.com/watch?v=hTacGMfL8lc&list=PLZoTAELRMXVNKtpy0U_Mx9N26w8n0hIbs
1. Spam SMS Classification
Deployed at - https://spam-sms-detector.herokuapp.com/
GitHub Link - https://github.com/anujvyas/Spam-SMS-Classifier-Deployment

2. Sentiment Analysis of Restaurant Reviews
Deployed at - https://restaurant-reviews-sentiment.herokuapp.com/
GitHub Link - https://github.com/anujvyas/Restaurant-Reviews-Sentiment-Analysis-Deployment

3. Movies Genre Classification
Deployed at - https://movie-genre-prediction.herokuapp.com/
GitHub Link - https://github.com/anujvyas/Movie-Genre-Prediction-Deployment

4. Diabetes Prediction
Deployed at - https://predicting-diabetes.herokuapp.com/
GitHub Link - https://github.com/anujvyas/Diabetes-Prediction-Deployment
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4 End To End Projects Till Deployment For Beginners In Data Science| All You Have To Do Is Learn

github link: https://github.com/krishnaik06/Dockers
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Deploy Machine Learning Models Using StreamLit Library- Data Science

github url: https://github.com/krishnaik06/Pandas-Profiling-EDA

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Perform Exploratory Data Analysis In Minutes- Data Science| Machine Learning

In this video I am going to discuss about pandas visual analysis where we will perform EDA in a single line of code
github: https://github.com/krishnaik06/pandas-visual-analysis
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Live Projects        :https://www.youtube.com/playlist?list=PLZoTAELRMXVOFnfSwkB_uyr4FT-327noK
Kaggle competition   :https://www.youtube.com/playlist?list=PLZoTAELRMXVPiKOxbwaniXjHJ02bdkLWy
Mongodb with Python  :https://www.youtube.com/playlist?list=PLZoTAELRMXVN_8zzsevm1bm6G-plsiO1I
MySQL With Python    :https://www.youtube.com/playlist?list=PLZoTAELRMXVMd3RF7p-u7ezEysGaG9JmO
Deployment Architectures:https://www.youtube.com/playlist?list=PLZoTAELRMXVOPzVJiSJAn9Ly27Fi1-8ac
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#eda
#pandavisualanalysis

Pandas Visual Analysis- Perform Exploratory Data Analysis In A Single Line Of Code🔥🔥🔥🔥

github: https://github.com/krishnaik06/VAEX_Big-Data

Last 2 days for the enrollment for Affordable Machine Learning And Deep Learning With Deployment Batch.
Ineuron.ai is launching a new Affordable Machine Learning And Deep Learning With Deployment Batch. The time duration of the course will be for 5 months and 3 months remote internship. This course also covers pyspark and provides you self paced course for Power BI and Tableau.
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How To Read And Process Huge Datasets in Seconds Using Vaex Library| Data Science| Machine Learning

In this video I am going to discuss about pandas visual analysis where we will perform EDA in a single line of code
github: https://github.com/krishnaik06/Dtale
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Live Projects        :https://www.youtube.com/playlist?list=PLZoTAELRMXVOFnfSwkB_uyr4FT-327noK
Kaggle competition   :https://www.youtube.com/playlist?list=PLZoTAELRMXVPiKOxbwaniXjHJ02bdkLWy
Mongodb with Python  :https://www.youtube.com/playlist?list=PLZoTAELRMXVN_8zzsevm1bm6G-plsiO1I
MySQL With Python    :https://www.youtube.com/playlist?list=PLZoTAELRMXVMd3RF7p-u7ezEysGaG9JmO
Deployment Architectures:https://www.youtube.com/playlist?list=PLZoTAELRMXVOPzVJiSJAn9Ly27Fi1-8ac
Amazon sagemaker     :https://www.youtube.com/playlist?list=PLZoTAELRMXVONh5mHrXowH6-dgyWoC_Ew

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#eda
#pandavisualanalysis
#dtale

D-Tale The Best Library To Perform Exploratory Data Analysis Using Single Line Of Code🔥🔥🔥🔥

In this video we will be understanding the important interview questions that are usually asked regarding LSupport Vector machines
It is must for every data science aspirants
github: https://github.com/krishnaik06/Interview-Prepartion-Data-Science
Data Science Interview Playlist: https://www.youtube.com/playlist?list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K-

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#datascienceprojects
#machinelearninginterviews
#deeplearninginterview
#datascienceinterviews
#computervision
#nlp

Interview Prep Day3-How To Prepare Support Vector Machines Important Questions In Interviews🔥🔥

After a mega start of the Unacademy Premier League, we are back with the second match - The Play-offs. UPL Play-off will have Prizes worth 3 Lakhs to be Won!
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Google Dataset Search is a search engine from Google that helps researchers locate online data that is freely available for use. Google Dataset Search complements Google Scholar, the company's search engine for academic studies and reports.

Google Dataset Search Engine url:https://datasetsearch.research.google.com/
Various Dataset Sources: https://www.youtube.com/watch?v=XcWFTEdERP0
⭐  Kite is a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I've been using Kite for a few months and I love it! https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=krishnaik&utm_content=description-only


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Mongodb with Python  :https://www.youtube.com/playlist?list=PLZoTAELRMXVN_8zzsevm1bm6G-plsiO1I
MySQL With Python    :https://www.youtube.com/playlist?list=PLZoTAELRMXVMd3RF7p-u7ezEysGaG9JmO
Deployment Architectures:https://www.youtube.com/playlist?list=PLZoTAELRMXVOPzVJiSJAn9Ly27Fi1-8ac
Amazon sagemaker     :https://www.youtube.com/playlist?list=PLZoTAELRMXVONh5mHrXowH6-dgyWoC_Ew


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#googledatasetsearch

Google Datasets Search Engine- Search All Datasets From One Place For Data Science,Machine Learning

<p>github Materials: https://github.com/krishnaik06/PCA-Geometrical-And-Mathematical-Intuition Principal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data. Many studies use the first two principal components in order to plot the data in two dimensions and to visually identify clusters of closely related data points. Principal component analysis has applications in many fields such as population genetics, microbiome studies, and atmospheric science.</p>

Machine Learning Full Course By Krish Naik

Machine Learning Full Course By Krish Naik

Chapters

Course Chapters