Machine Learning

S.no	Lecture	Notes
1	Python Basics	Here
2	Conditionals, Loops and Functions	Here
3	Lists and Dictionaries	Here
4	2D Lists and Numpy	Here
5	Pandas	Here
6	Plotting Graphs	Here
7	Introduction to Machine Learning	Here
8	Linear Regression	Here
9	Multi-variable Regression and Gradient Descent	Here
10	Project - Gradient Descent
11	Logistic Regression	Here
12	Project - Logistic Regression
13	Classification Measures	Here
14	Decision Trees - 1
15	Decision Trees - 2
16	Project - Decision Tree Implementation
17	Feature Scaling
18	Random Forests
19	Naive Bayes
20	Project - Text Classification
21	K Nearest Neighbours
22	Support Vector Machines
23	Principal Component Analysis
24	Principal Component Analysis - 2
25	Project - CIFAR10
26	Natural Language Processing - 1
27	Natural Language Processing - 2
28	Project - Twitter Sentiment Analysis
29	Git
30	Neural Networks - 1
31	Neural Networks - 2
32	Tensorflow
33	Keras
34	Convolutional Neural Networks - 1
35	Convolutional Neural Networks - 2
36	Recurrent Neural Networks
37	LSTM
38	Unsupervised Learning - 1
39	Unsupervised Learning - 2

Additional References