This contains all the project descriptions, datasets, solutions from my Post Graduate Program in AI-ML, offered by UT Austin and Great Lakes Institute of Management. Please follow this sequence for an efficient learning:
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Supervised Learning
A. Linear Regression
B. Logistic Regression
C. Naive Bayes and K-Nearest Neighbours
D. Support Vector Machines
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Ensemble Learning
A. Decision Trees
B. Ensemble Techniques
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Unsupervised Learning
A. K-Means clustering
B. Principle Component Analysis
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Featurization, Model Selection and Tuning (Feature Engineering)
A. Regularization, Cross Validation
B. Hyperparameter Tuning, Pipeline
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Recommendation Systems
A. Content Based, Popularity Based
B. Matrix Factorization, Collaborative Filtering, SVD
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Introduction to Neural Networks
A. Introduction
B. Building Blocks
C. Babysitting the Neural Network
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Computer Vision
List of different learning resources Python Basics -
Google's Python Class - https://developers.google.com/edu/python/
Python Documentation - https://docs.python.org/3/tutorial/
A Byte of Python - https://python.swaroopch.com/
Data Analysis using Python -https://github.com/ajaymache/data-analysis-using-python
Official technical explanation of functions - https://docs.python.org/3/library/index.html
Survey of Python syntax, datatypes - https://diveintopython3.net/
The Official Python Tutorial - https://docs.python.org/3/tutorial/
Reserved Keywords in Python - https://docs.python.org/3.0/reference/lexical_analysis.html#id8
Style Guide for Python Code- https://www.python.org/dev/peps/pep-0008/
Python Tools for Visual Studio https://microsoft.github.io/PTVS/
Statistics - http://onlinestatbook.com/2/probability/basic.html
ISLR -Introduction to Statistical Learning
Machine Learning-
ML using Python - https://github.com/ageron/handson-ml
Visual intro to machine learning - http://www.r2d3.us/visual-intro-to-machine-learning-part-1/
http://www.r2d3.us/visual-intro-to-machine-learning-part-2/
Scikit Learn user Guide - https://scikit-learn.org/stable/user_guide.html
Google Dataset Search - https://datasetsearch.research.google.com/ Learn and use machine learning - https://www.tensorflow.org/tutorials/keras
Deep Learning-
Deep Learning with Python-https://github.com/fchollet/deep-learning-with-python-notebooks
Getting started with TensorFlow -https://www.tensorflow.org/tutorials/
Natural Language Processing with Python- http://www.nltk.org/book/
Documentations-
Python Documentation-https://www.python.org/doc/
Tensorflow Guide -https://www.tensorflow.org/guide
Keras Documentation -https://keras.io/
Scikit Learn Documentation -https://scikit-learn.org/stable/documentation.html
NLTK Documentation- https://www.nltk.org/