Adrenaline-Education

Course 3 of 4 in this specialization

Develop Deep Learning Models for Complex Tasks

Coming soon 25 topics Self-paced · Online
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Where this comes from

Built from the Wiley title of the same name — professionally edited, technically reviewed, and already relied on by people doing this work.

Source ISBN 9781119543039

How it was built

Sejal Learning Systems rebuilt the book as a course: objectives first, then short video, worked examples, and practice with real feedback. It runs on Coursera at your own pace, with a certificate on completion.

Develop Deep Learning Models for Complex Tasks is a self-paced online course built from the Wiley title of the same name.

What this course covers

  • Introduction
  • Part 1: Discovering Deep Learning
  • Chapter 1: Introducing Deep Learning
  • Chapter 2: Introducing the Machine Learning Principles
  • Chapter 3: Getting and Using Python
  • Chapter 4: Leveraging a Deep Learning Framework
  • Part 2: Considering Deep Learning Basics
  • Chapter 5: Reviewing Matrix Math and Optimization
  • Chapter 6: Laying Linear Regression Foundations
  • Chapter 7: Introducing Neural Networks
  • Chapter 8: Building a Basic Neural Network
  • Chapter 9: Moving to Deep Learning
  • Chapter 10: Explaining Convolutional Neural Networks
  • Chapter 11: Introducing Recurrent Neural Networks
  • Part 3: Interacting with Deep Learning
  • Chapter 12: Performing Image Classification
  • Chapter 13: Learning Advanced CNNs
  • Chapter 14: Working on Language Processing
  • Chapter 15: Generating Music and Visual Art
  • Chapter 16: Building Generative Adversarial Networks
  • Chapter 17: Playing with Deep Reinforcement Learning
  • Part 4: The Part of Tens
  • Chapter 18: Ten Applications that Require Deep Learning
  • Chapter 19: Ten Must-Have Deep Learning Tools
  • Chapter 20: Ten Types of Occupations that Use Deep Learning