Course curriculum

    1. Segment - 01 - Introduction

    2. Segment - 02 - Get Started With the Python Data Science Environment: Anaconda

    3. Segment - 03 - Anaconda for Mac Users

    4. Segment - 04 - The iPython Environment

    5. Segment - 05 - Why PyTorch?

    6. Segment - 06 - Install PyTorch

    7. Segment - 07 - Further Installation Instructions for Mac

    8. Segment - 08 - Working With CoLabs

    1. Segment - 09 - Python Packages for Data Science

    2. Segment - 10 - Introduction to Numpy

    3. Segment - 11 - Create Numpy Arrays

    4. Segment - 12 - Numpy Operations

    5. Segment - 13 - Numpy for Basic Vector Arithmetic

    6. Segment - 14 - Numpy for Basic Matrix Arithmetic

    7. Segment - 15 - PyTorch Basics: What Is a Tensor?

    8. Segment - 16 - Explore PyTorch Tensors and Numpy Arrays

    9. Segment - 17 - Some Basic PyTorch Tensor Operations

    1. Segment - 18 - Read in CSV Data

    2. Segment - 19 - Read in Excel Data

    3. Segment - 20 - Basic Data Exploration With Pandas

    1. Segment - 21 - Ordinary Least Squares (OLS) Regression - Theory

    2. Segment - 22 - OLS Linear Regression - Without PyTorch

    3. Segment - 23 - OLS Linear Regression From First Principles - Theory

    4. Segment - 24 - OLS Linear Regression From First Principles - Without PyTorch

    5. Segment - 25 - OLS Linear Regression From First Principles - With PyTorch

    6. Segment - 26 - More OLS With PyTorch

    7. Segment - 27 - Generalized Linear Models (GLMs) - Theory

    8. Segment - 28 - Logistic Regression - Without PyTorch

    9. Segment - 29 - Logistic Regression - With PyTorch

    1. Segment - 30 - Introduction

    2. Segment - 31 - PyTorch ANN Syntax

    3. Segment - 32- What Are Activation Functions?

    4. Segment - 33 - More on Back Propagation

    5. Segment - 34 - Bringing them Together

    6. Segment - 35 - Setting up ANN Analysis with PyTorch

    7. Segment - 36 - DNN Analysis with PyTorch

    8. Segment - 37 - More DNNs

    9. Segment - 38 - DNNs For Identifying Credit Card Fraud

    10. Segment - 39 - An Explanation of Accuracy Metrics

    1. Segment - 40 - What are Images?

    2. Segment - 41 - Read in Images in Python

    3. Segment - 42 - Basic Image Conversions

    4. Segment - 43 - Why AI and Deep Learning?

    5. Segment - 44 - Artificial Neural Networks (ANN) For Image Classification

    6. Segment - 45 - Deep Neural Networks (DNN) For Image Classification

About this course

  • Free
  • 50 lessons
  • 6.5 hours of video content