Course curriculum

    1. Segment - 01 - Introduction

    2. Segment - 02 - Why AI and Deep Learning?

    3. Segment - 03 - Get Started with the Python Data Science Environment: Anaconda

    4. Segment - 04 - Anaconda for Mac Users

    5. Segment - 05 - The iPython Environment

    1. Segment - 06 - Python Packages for Data Science

    2. Segment - 07 - Introduction to Numpy

    3. Segment - 08 - Create Numpy Arrays

    4. Segment - 09 - Numpy Operations

    5. Segment - 10 - Numpy for Basic Matrix Arithmetic

    6. Segment - 11 - Introduction to Pandas

    7. Segment - 12 - Read in Data from CSV

    8. Segment - 13 - Read in Data from Excel

    9. Segment - 14 - Basic Data Cleaning

    1. Segment - 15 - What is Keras?

    2. Segment - 16 - Keras Installation-Windows

    3. Segment - 17 - Keras Installation on Mac OS

    1. Segment - 18 - What is Machine Learning?

    1. Segment - 19 - Theory Behind ANN (Artificial Neural Network) and DNN (Deep Neural Networks)

    2. Segment - 20 - Activation Functions

    3. Segment - 21 - Multi Layer Perceptron (MLP) with Keras

    4. Segment - 22 - What is Backpropagation?

    5. Segment - 23 - Keras MLP for Binary Classification

    6. Segment - 24 - Accuracy Assessment for Binary Classification

    7. Segment - 25 - Keras MLP for Multiclass Classification

    8. Segment - 26 - Keras MLP for Regression

    1. Segment - 27 - What is Unsupervised Learning?

    2. Segment - 28 - Autoencoders for Unsupervised Classification

    3. Segment - 29 - Autoencoders in Keras (Sparsity Constraints)

    4. Segment - 30 - Autoencoders in Keras (Simple)

About this course

  • Free
  • 37 lessons
  • 4 hours of video content