This is the sample code repository for the book Build Deeper: The Path to Deep Learning.
This repository contains the code examples discussed the following chapters of the book:
- Chapter 5 : Build Your First Deep Learning Model
- Chapter 6 : Looking Under the Hood
- Chapter 7 : What Next?
- Chapter 8 : Build Our Own Image Classifier with Transfer Learning
- Chapter 9 : Bonus – Getting Started with Computer Vision
- Thimira Amaratunga*
Deep Learning is no longer shrouded in mystery. In fact, it is the emerging new frontier – the bleeding edge – of AI. It is increasingly achieving superhuman feats and evolving beyond human comprehension. From image and voice recognition, to AI personal assistants and self-driving cars, achievements and breakthroughs that were once mere science fiction are now becoming our reality. Top tech companies world over are all in the game – trying to win the race for AI, with Deep Learning.
The question now is, do you want to simply be a bystander in this new-age game?
The art of building deep learning systems is becoming easier every day.
This book can be your guide to discovering it yourself.
Build Deeper is a complete and practical guide that can help you take the first few steps in deep learning. It will guide you step-by-step, from understanding the basic concepts, to building your first practical application.
It covers:
- What Deep Learning is, and where it fits with Artificial Intelligence and Machine Learning.
- How Deep Learning came to be, its predecessors, and the path it took to evolve into what it is today.
- The important milestones it has passed through the years, and the impact they had on the field.
- What tools are available for us to learn and build deep learning applications, and how to set them up: Python, TensorFlow, Theano, Keras, and more, on any OS of your choosing: Windows, Linux, or Mac OS.
- Building our first simple deep learning model.
- The internal workings of a deep learning model.
- Using more advanced topics such as Data Augmentation, Transfer Learning, Bottleneck Features, and Fine Tuning to build a practical deep learning application.
- Getting started with Computer Vision.
All you need now is a little enthusiasm … who knows where it will take you!
Go a little deeper to discover …
The Build Deeper: The Path to Deep Learning - released in January 2019 - is the successor for the earlier book Build Deeper: Deep Learning Beginners' Guide which was released in August 2017.