Books & Videos

Table of Contents

Chapter: Why Design For Machine Learning Is Different

Course Intro

01m 43s

About The Author

01m 5s

Boolean Vs Fuzzy Logic

02m 26s

Explicit Programming Vs Experiential Training In Machine Learning

03m 18s

Procedural Precision Vs Intuitive Approximation With Machine Learning

02m 12s

Finding The Right Tool For The Job

01m 5s

Chapter: What Is Machine Learning?

Deductive And Inductive Reasoning

01m 20s

Mechanical Induction

04m 29s

The Major Types Of Learning Algorithms

04m 56s

What Is Deep Learning?

02m 38s

Building Intuition For Machine Learning Problems

05m 41s

Chapter: Getting Started With Machine Learning Workflows

Preliminary Look At The Stages Of A Machine Learning Workflow

04m 57s

Why Machine Learning Requires Special Tools And Workflows

03m 38s

Streamlining Machine Learning Workflows With Docker

01m 44s

Getting Started With Docker

01m 24s

Getting Started With Launchbot

03m 14s

Getting Started With Jupyter Notebooks

02m 37s

Chapter: Getting Started With Machine Learning Development

Getting Started With TensorFlow

04m 25s

Setting Up TensorFlow

00m 37s

Graphs And Sessions In TensorFlow

03m 25s

Basic Operations In TensorFlow

02m 43s

Working With Data In TensorFlow

03m 42s

Building And Training A Simple Neural Network In TensorFlow

07m 42s

Visualizing A Simple Neural Network In TensorFlow

02m 20s

Chapter: Going Deeper With Machine Learning Development

Saving And Restoring Models In TensorFlow

01m 41s

The Dark Art Of Neural Network Configuration

04m 11s

Overfitting And Other Learning Difficulties

04m 32s

Improving Learning Quality

04m 51s

Working With The Inception Image Recognizer In TensorFlow

03m 19s

Performing Transfer Learning On The Inception Image Recognizer In TensorFlow

05m 22s

Chapter: Integrating Machine Learning Systems Into User-Facing Software

Building A User-Facing Image Recognition Web Application

06m 3s

Chapter: Reflecting Upon The Design Landscape

Reflecting Upon Design Landscape

04m 42s

Chapter: Design Opportunities

Parsing Complex Information

07m 51s

Creating Dialogue

08m 5s

Chapter: Design Challenges

Designing For Uncertainty

02m 36s

Masking Faulty Assumptions

03m 5s

Creating Sanity Checks

02m 44s

Chapter: How To Continue Your Study Of Machine Learning

Resources For The Further Study Of Machine Learning

00m 54s

Staying Up-To-Date With Advancements In The Field

01m 13s

Emerging Opportunities For Machine-Learning-Enhanced Design

01m 56s

Chapter: Conclusion

Wrap Up And Thank You

00m 44s