Deep Learning for Beginners
This book is for beginners who are looking for a strong foundation to build deep learning models from scratch. You will test your understanding of the concepts and measure your progress at the end of each chapter. You will have a firm understanding of deep learning and will be able to identify which algorithms are appropriate for different tasks.
Offered by
Difficulty Level
Intermediate
Completion Time
14h24m
Language
English
About Book
Who Is This Book For?
This book is for aspiring data scientists and deep learning engineers who want to get started with the fundamentals of deep learning and neural networks. Although no prior knowledge of deep learning or machine learning is required, familiarity with linear algebra and Python programming is necessary to get started.
Deep Learning for Beginners
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 14h24m total length
Introduction to Machine Learning
Setup and Introduction to Deep Learning Frameworks
Preparing Data
Learning from Data
Training a Single Neuron
Training Multiple Layers of Neurons
Autoencoders
Deep Autoencoders
Variational Autoencoders
Restricted Boltzmann Machines
Deep and Wide Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
Generative Adversarial Networks
Final Remarks on The Future of Deep Learning
Related Resources
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