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Machine Learning Full Course By Krish Naik

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Curriculum
1. Complete Road Map To Be Expert In Python- Follow My Way
2. Complete Roadmap To Follow To Prepare Machine Learning With All Videos And Materials
3. Tutorial 1- Anaconda Installation and Python Basics
4. Why Python is the Best Programming Language For Machine Learning?
5. Tutorial 2 - Python List and Boolean Variables
6. Tutorial 3- Python Sets, Dictionaries and Tuples
7. Tutorial 4 - Numpy and Inbuilt Functions Tutorial
8. Tutorial 5- Pandas, Data Frame and Data Series Part-1
9. Tutorial 6- Pandas,Reading CSV files With Various Parameters- Part 2
10. Tutorial 7- Pandas-Reading JSON,Reading HTML, Read PICKLE, Read EXCEL Files- Part 3
11. Tutorial 8- Matplotlib (Simple Visualization Library)
12. Tutorial 9- Seaborn Tutorial- Distplot, Joinplot, Pairplot Part 1
13. Tutorial 10- Seaborn- Countplot(), Violinplot(), Boxplot()- Part2
14. How To Become Expertise in Exploratory Data Analysis
15. Tutorial 11-Exploratory Data Analysis(EDA) of Titanic dataset
16. Tutorial 12- Python Functions, Positional and Keywords Arguments
17. Tutorial 15- Map Functions using Python
18. Tutorial 13- Python Lambda Functions
19. Tutorial 16- Filter Functions In Python
20. Tutorial 17- Python List Comprehension
21. Tutorial 18- Python Advanced String Formatting
22. Tutorial 19- Python Iterables vs Iterators
23. Tutorial 20- How To Import All Important Python Data Science Libraries Using Pyforest
24. Tutorial 21- Python OOPS Tutorial- Classes, Variables, Methods and Objects
25. Advanced Python- Exception Handling Detailed Explanation In Python
26. Advanced Python Series- Custom Exception Handling In Python
27. Advance Python Series- Public Private And Protected Access Modifiers
28. Advance Python Series- Inheritance In Python
29. Tutorial 22-Univariate, Bivariate and Multivariate Analysis- Part1 (EDA)-Data Science
30. Tutorial 23-Univariate, Bivariate and Multivariate Analysis- Part2 (EDA)-Data Science
31. Tutorial 24- Histogram in EDA- Data Science
32. Tutorial 24-Z Score Statistics Data Science
33. Tutorial 25- Probability Density function and CDF- EDA-Data Science
34. Tutorial 26- Linear Regression Indepth Maths Intuition- Data Science
35. Tutorial 27- Ridge and Lasso Regression Indepth Intuition- Data Science
36. Tutorial 28- Ridge and Lasso Regression using Python and Sklearn
37. Multiple Linear Regression using python and sklearn
38. Tutorial 28-MultiCollinearity In Linear Regression- Part 2
39. Machine Learning-Bias And Variance In Depth Intuition| Overfitting Underfitting
40. Tutorial 29-R square and Adjusted R square Clearly Explained| Machine Learning
41. Tutorial 31- Hypothesis Test, Type 1 Error, Type 2 Error
42. What Is P Value In Statistics In Simple Language?
43. Tutorial 32- All About P Value,T test,Chi Square Test, Anova Test and When to Use What?
44. Tutorial 33- P Value,T test, Correlation Implementation with Python- Hypothesis Testing
45. Tutorial 33- Chi Square Test Implementation with Python- Hypothesis Testing- Part 2
46. Tutorial 34- Performance Metrics For Classification Problem In Machine Learning- Part1
47. Tutorial 35- Logistic Regression Indepth Intuition- Part 1| Data Science
48. Tutorial 36- Logistic Regression Indepth Intuition- Part 2| Data Science
49. Tutorial 36- Logistic Regression Mutliclass Classification(OneVsRest)- Part 3| Data Science
50. Tutorial 37: Entropy In Decision Tree Intuition
51. Tutorial 38- Decision Tree Information Gain
52. Tutorial 39- Gini Impurity Intuition In Depth In Decision Tree
53. Tutorial 40- Decision Tree Split For Numerical Feature
54. Advance House Price Prediction- Exploratory Data Analysis- Part 1
55. Advance House Price Prediction- Exploratory Data Analysis- Part 2
56. Advance House Price Prediction-Feature Engineering Part 1
57. Advance House Price Prediction-Feature Engineering Part 2
58. Advance House Price Prediction-Feature Selection
59. Tutorial 41-Performance Metrics(ROC,AUC Curve) For Classification Problem In Machine Learning Part 2
60. Performance Metrics On MultiClass Classification Problems
61. K Nearest Neighbor classification with Intuition and practical solution
62. K Nearest Neighbour Easily Explained with Implementation
63. Tutorial 42 - Ensemble: What is Bagging (Bootstrap Aggregation)?
64. Tutorial 43-Random Forest Classifier and Regressor
65. Tutorial 45-Handling imbalanced Dataset using python- Part 1
66. Tutorial 46-Handling imbalanced Dataset using python- Part 2
67. Hyperparameter Optimization for Xgboost
68. What is AdaBoost (BOOSTING TECHNIQUES)
69. Visibility Climate Prediction- You Can Add This In Your Resume
70. Euclidean Distance and Manhattan Distance
71. K Means Clustering Intuition
72. Hierarchical Clustering intuition
73. DBSCAN Clustering Easily Explained with Implementation
74. Silhouette (clustering)- Validating Clustering Models- Unsupervised Machine Learning
75. Curse of Dimensionality Easily explained| Machine Learning
76. Dimensional Reduction| Principal Component Analysis
77. Principle Component Analysis (PCA) using sklearn and python
78. What is Cross Validation and its types?
79. Tutorial 42-How To Find Optimal Threshold For Binary Classification - Data Science
80. Tutorial 47- Bayes' Theorem| Conditional Probability- Machine Learning
81. Tutorial 48- Naive Bayes' Classifier Indepth Intuition- Machine Learning
82. Tutorial 49- How To Apply Naive Bayes' Classifier On Text Data (NLP)- Machine Learning
83. Support Vector Machine (SVM) Basic Intuition- Part 1| Machine Learning
84. Maths Intuition Behind Support Vector Machine Part 2 | Machine Learning Data Science
85. SVM Kernels In-depth Intuition- Polynomial Kernels Part 3 | Machine Learning Data Science
86. SVM Kernal- Polynomial And RBF Implementation Using Sklearn- Machine Learning
87. Gradient Boosting In Depth Intuition- Part 1 Machine Learning
88. Gradient Boosting Complete Maths Indepth Intuiton Explained| Machine Learning- Part2
89. Xgboost Classification Indepth Maths Intuition- Machine Learning Algorithms🔥🔥🔥🔥
90. Xgboost Regression In-Depth Intuition Explained- Machine Learning Algorithms 🔥🔥🔥🔥
91. Data Science In Medical-Live Tracking Of CO--VID Cases In India using Python
92. Perform EDA In Seconds With Visualization Using SweetViz Library
93. 4 End To End Projects Till Deployment For Beginners In Data Science| All You Have To Do Is Learn
94. Deploy Machine Learning Models Using StreamLit Library- Data Science
95. Perform Exploratory Data Analysis In Minutes- Data Science| Machine Learning
96. Pandas Visual Analysis- Perform Exploratory Data Analysis In A Single Line Of Code🔥🔥🔥🔥
97. How To Read And Process Huge Datasets in Seconds Using Vaex Library| Data Science| Machine Learning
98. D-Tale The Best Library To Perform Exploratory Data Analysis Using Single Line Of Code🔥🔥🔥🔥
99. Interview Prep Day3-How To Prepare Support Vector Machines Important Questions In Interviews🔥🔥
100. Google Datasets Search Engine- Search All Datasets From One Place For Data Science,Machine Learning
101. How To Run Flask In Google Colab
102. Time Series Forecasting Using Facebook FbProphet
103. Performance Metrics Interview Questions- Data Science
104. How To Perform Post Pruning In Decision Tree? Prevent Overfitting- Data Science
105. How To Train Machine Learning Model Using CPU Multi Cores
106. Step By Step Process To Learn Machine Learning Algorithm Efficiently
107. Data Science Is Just Not About Model Building
108. How To Interpret The ML Model? Is Your Model Black Box? Lime Library
109. 6 Healthcare End To End Machine Learning Projects- Credits Devansh and Bedanta
110. Overfitting, Underfitting And Data Leakage Explanation With Simple Example
111. What Is API? Application Programming Interface And Why It Is Important-Data Science
112. 500+ Machine Learning And Deep Learning Projects All At One Place
113. Google Colab Pro Vs Colab Free- Benefits Of Using Colab Pro- How To Access From India
114. Advance Python Series-Magic Methods In Classes
115. Advanced Python Series- Assert Statement In Python
116. How To Speed Up Pandas By 4X Times- Modin Pandas Library
117. TextBlob Library In Python For Natural Language Processing
118. 3000+ Research Datasets For Machine Learning Researchers By Papers With Code
119. Introduction To MLflow-An Open Source Platform for the Machine Learning Lifecycle
120. Amazing Data Science End To End Project From Starters In ML and Deep Learning- Agriculture Domain
121. Lux - Python Library for Intelligent Visual Discovery
122. Texthero-Text Preprocessing, Representation And Visualization From Zero to Hero.
123. Colab Pro Now Available In India, Brazil, France, Thailand,Japan,UK- BOON FOR Data Science Aspirants
124. Rainfall Prediction- Converting A Kaggle Project to End To End Machine Learning Project
125. PyWebIO- Creating WebAPP Using Python Without Using HTML And JS
126. Creating BMI Calculator Web APP Using Python And PyWebIO
127. Deployment Of ML Models Using PyWebIO And Flask
128. Shapash- Python Library To Make Machine Learning Interpretable
129. Difference Between fit(), transform(), fit_transform() and predict() methods in Scikit-Learn
130. EvalML AutoML Library To Automate Feature Engineering, Feature Selection,Model Creation And Tuning
131. Lazy Predict Python- Understanding Which Models Works Well Without Any Tuning
132. How To Automate NLP Tasks Using EvalML Library
133. Gradio Library-Interfaces for your Machine Learning Models
134. Comparing Transfer Learning Models Using Gradio
135. Introduction To Machine Learning And Deep Learning For Starters
136. Numba Library- Let's Make Python Faster
137. Deployment Of ML Models Using PyWebIO And Flask In Heroku
138. All Automated EDA Libraries All At One Place
139. Discussing All The Types Of Feature Transformation In Machine Learning
140. Automating Web Scrapping Using AutoScraper Library
141. Automating WebScraping Amazon Ecommerce Website Using AutoScrapper
142. AutoScraper and Flask: Create an API From Amazon Website in Less Than 10 Minutes
143. Autoviz-Automatically Visualize Any Dataset With Single Line Of Code
144. AutoScraper- Scrap Images From Amazon Ecommerce- End To End Web Scraping Application
145. All Type Of Cross Validation With Python All In 1 Video
146. DataPrep Library- Perform Faster EDA Within No Time
147. Time Series Forecasting Made Easy Using Dart Library - Perform Multivariate Forecasting In No Time
148. FLAML - Fast and Lightweight AutoML Library By Microsoft
149. Tutorial on Automated Machine Learning using MLBox
150. Definition Of Bias And Variance In Machine Learning- Interview Question
151. Elasticnet Regression Machine Learning Algorithm Explained In Depth
152. Out Of Bag Evaluation(OOB) And OOB Score Or Error In Random Forest
153. PCA Indepth Geometric And Mathematical InDepth Intuition ML Algorithms
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Complete Road Map To Be Expert In Python- Follow My Way

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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 Visit https://krishnaik.in Python AI Tech news : https://www.youtube.com/playlist?list=PLTDARY42LDV6iFI3Dd3oNf6oIvuJs_EKX Python With Complete Ml playlist: https://www.youtube.com/playlist?list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more https://www.youtube.com/channel/UCNU_lfiiWBdtULKOw6X0Dig/join Please do subscribe my other channel too https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw ----------------------------------------------------------------------------------------------------------------------- ►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

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