INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools
  • Introduction to the Course
  • Data and Scripts For the Course
  • Python Data Science Environment
  • For Mac Users
  • Introduction to IPython
  • Written Tensorflow Installation Instructions
  • Install Keras on Windows 10
  • Install Keras on Mac
  • Written Keras Installation Instructions
Introduction to Python Data Science Packages
  • Python Packages for Data Science
  • Introduction to Numpy
  • Create Numpy Arrays
  • Numpy Operations
  • Numpy for Statistical Operation
  • Introduction to Pandas
  • Read in Data from CSV
  • Read in Data from Excel
  • Basic Data Cleaning
Introduction to TensorFlow
  • A Brief Touchdown
  • A Brief Touchdown: Computational Graphs
  • Common Mathematical Operators in Tensorflow
  • A Tensorflow Session
  • Interactive Tensorflow Session
  • Constants and Variables in Tensorflow
  • Placeholders in Tensorflow
Introduction to Keras
  • What is Keras
Some Preliminary Tensorflow and Keras Applications
  • Theory of Linear Regression (OLS)
  • OLS From First Principles
  • Visualize the Results of OLS
  • Multiple Regression With Tensorflow-Part 1
  • Estimate With Tensorflow Estimators
  • Multiple Regression With Tensorflow Estimators
  • More on Linear Regressor Estimator
  • GLM: Generalized Linear Model
  • Linear Classifier For Binary Classification
  • Accuracy Assessment For Binary Classification
  • Linear Classification with Binary Classification With Mixed Predictors
  • Softmax Classification With Tensorflow
Some Basic Concepts
  • What is Machine Learning?
  • Theory Behind ANN (Artificial Neural Network) and DNN (Deep Neural Networks)
Unsupervised Learning With Tensorflow and Keras
  • What is Unsupervised Learning?
  • Autoencoders for Unsupervised Classification
  • Autoencoders in Tensorflow (Binary Class Problem)
  • Autoencoders in Tensorflow (Multiple Classes)
  • Autoencoders in Keras (Sparsity Constraints)
  • Autoencoders in Keras (Simple)
  • Deep Autoencoder With Keras
Neural Network for Tensorflow & Keras
  • Multi Layer Perceptron (MLP) with Tensorflow
  • Multi Layer Perceptron (MLP) With Keras
  • Keras MLP For Binary Classification
  • Keras MLP for Multiclass Classification
  • Keras MLP for Regression
Deep Learning For Tensorflow & Keras
  • What is Artificial Intelligence?
  • Deep Neural Network (DNN) Classifier With Tensorflow
  • Deep Neural Network (DNN) Classifier With Mixed Predictors
  • Deep Neural Network (DNN) Regression With Tensorflow
  • Wide & Deep Learning (Tensorflow)
  • DNN Classifier With Keras
  • DNN Classifier With Keras-Example 2
Convolution Neural Network (CNN) For Image Analysis
  • Introduction to CNN
  • Implement a CNN for Multi-Class Supervised Classification
  • Activation Functions
  • More on CNN
  • Pre-Requisite For Working With Imagery Data
  • CNN on Image Data-Part 1
  • CNN on Image Data-Part 2
  • More on TFLearn
  • CNN Workflow for Keras
  • CNN With Keras
  • CNN on Image Data with Keras-Part 1
  • CNN on Image Data with Keras-Part 2
Autoencoders With Convolution Neural Networks (CNN)
  • Autoencoders for With CNN- Tensorflow
  • Autoencoders for With CNN- Keras
Recurrent Neural Networks (RNN)
  • Theory Behind RNNs
  • LSTM For Time Series Data
  • LSTM for Predicting Stock Prices
Miscellaneous Section
  • Use Colabs for Jupyter Data Science
  • Github