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Machine Learning

  • #c5f015 Complete
S.no Lecture Status Notes
1 Python Basics #c5f015 Here
2 Conditionals, Loops and Functions #c5f015 Here
3 Lists and Dictionaries #c5f015 Here
4 2D Lists and Numpy #c5f015 Here
5 Pandas #c5f015 Here
6 Plotting Graphs #c5f015 Here
7 Introduction to Machine Learning #c5f015 Here
8 Linear Regression #c5f015 Here
9 Multi-variable Regression and Gradient Descent #c5f015 Here
10 Project - Gradient Descent #c5f015
11 Logistic Regression #c5f015 Here
12 Project - Logistic Regression #c5f015
13 Classification Measures #c5f015 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

  1. Visualising Decision Trees Using Scikit learn and Graphviz

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Code written while learning and implementing machine learning algorithms during the course at coding ninjas

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