Search icon Close icon
Search icon
Subscription
0
Cart icon
Close icon
You have no products in your basket yet
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Deep Learning for Beginners

You're reading from  Deep Learning for Beginners

Product type Book
Published in Sep 2020
Publisher Packt
ISBN-13 9781838640859
Pages 432 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Dr. Pablo Rivas Dr. Pablo Rivas
Profile icon Dr. Pablo Rivas
LinkedIn
Dr. Pablo Rivas is an assistant professor of computer science at Baylor University in Texas. He worked in industry for a decade as a software engineer before becoming an academic. He is a senior member of the IEEE, ACM, and SIAM. He was formerly at NASA Goddard Space Flight Center performing research. He is an ally of women in technology, a deep learning evangelist, machine learning ethicist, and a proponent of the democratization of machine learning and artificial intelligence in general. He teaches machine learning and deep learning. Dr. Rivas is a published author and all his papers are related to machine learning, computer vision, and machine learning ethics. Dr. Rivas prefers Vim to Emacs and spaces to tabs.
See other products by Dr. Pablo Rivas

Table of Contents (20) Chapters

Preface 1. Section 1: Getting Up to Speed
2. Introduction to Machine Learning 3. Setup and Introduction to Deep Learning Frameworks 4. Preparing Data 5. Learning from Data 6. Training a Single Neuron 7. Training Multiple Layers of Neurons 8. Section 2: Unsupervised Deep Learning
9. Autoencoders 10. Deep Autoencoders 11. Variational Autoencoders 12. Restricted Boltzmann Machines 13. Section 3: Supervised Deep Learning
14. Deep and Wide Neural Networks 15. Convolutional Neural Networks 16. Recurrent Neural Networks 17. Generative Adversarial Networks 18. Final Remarks on the Future of Deep Learning 19. Other Books You May Enjoy

Questions and answers

  1. Does Colab run on my personal computer?

No, it runs in the cloud, but with some skill and setup, you could connect it to your own personal cloud.

  1. Does Keras use GPUs?

Yes. Since Keras runs on TensorFlow (in the setup of this book) and TensorFlow uses GPUs, then Keras also does.

  1. What are the two main coding paradigms in Keras?

(A) Sequential model; (B) Functional API.

  1. Why do we care about Dopamine?

Because there are only a few reinforcement learning frameworks you can trust out there, and Dopamine is one of them.

lock icon The rest of the chapter is locked
arrow left Previous Chapter
Chapter 1 of 20
Next Chapter arrow right
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Sign up now
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Start free trial
Renews at $15.99/month. Cancel anytime}

Authors (1)

Profile icon Dr. Pablo Rivas
LinkedIn
Dr. Pablo Rivas is an assistant professor of computer science at Baylor University in Texas. He worked in industry for a decade as a software engineer before becoming an academic. He is a senior member of the IEEE, ACM, and SIAM. He was formerly at NASA Goddard Space Flight Center performing research. He is an ally of women in technology, a deep learning evangelist, machine learning ethicist, and a proponent of the democratization of machine learning and artificial intelligence in general. He teaches machine learning and deep learning. Dr. Rivas is a published author and all his papers are related to machine learning, computer vision, and machine learning ethics. Dr. Rivas prefers Vim to Emacs and spaces to tabs.
Read more
See other products by Dr. Pablo Rivas

Other recommended products

Related to this chapter
Left arrow icon
Machine Learning for Healthcare Analytics Projects
Machine Learning for Healthcare Analytics Projects
Machine Learning in the healthcare domain is booming because of its abilities to provide accurate and stabilized techniques. This book is packed with new methodologies to create efficient solutions for healthcare analytics. We will build five end-to-end projects to evaluate the efficiency of AI apps to carry out simple-to-complex healthcare analytics tasks.
Oct 2018 4 hours 28 minutes
Deep Learning with Hadoop
Deep Learning with Hadoop
Feb 2017 6 hours 52 minutes
Hands-On Deep Learning Algorithms with Python
Hands-On Deep Learning Algorithms with Python
This book introduces basic-to-advanced deep learning algorithms used in a production environment by AI researchers and principal data scientists; it explains algorithms intuitively, including the underlying math, and shows how to implement them using popular Python-based deep learning libraries such as TensorFlow.
Jul 2019 17 hours 4 minutes
Keras Deep Learning Cookbook
Keras Deep Learning Cookbook
This book gives you a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning. It presents a unique problem-solution approach to tackle various problems in training different types of neural networks while taking care of the speed and accuracy of these models
Oct 2018 8 hours 24 minutes
Python Deep Learning Cookbook
Python Deep Learning Cookbook
Deep Learning is a rapidly evolving field of Machine Learning science which gives machines the ability to learn from information. This book contains detailed recipes to tackle with the common and not so common problems while dealing with deep learning algorithms and models in Python. You will benefit from this book by finding technical solutions to the issues presented, along with a detailed explanation of the solutions, and a discussion on corresponding pros and cons of implementing the proposed solution using Theano, Tensorflow, MXNet, and Keras. You'll come across recipes on data pre-processing, network models and topologies, supervised and unsupervised learning presented in a “solution to problem” fashion.
Oct 2017 11 hours 0 minutes
TensorFlow 2.0 Computer Vision Cookbook
TensorFlow 2.0 Computer Vision Cookbook
This book covers recipes for solving various computer vision tasks using TensorFlow, taking you through all the tips and tricks you need to overcome any challenges that you may face while building various computer vision applications. You will discover machine learning techniques to solve problems in image processing, feature extraction, and more.
Feb 2021 18 hours 4 minutes
Neural Network Projects with Python
Neural Network Projects with Python
This book contains practical implementations of several deep learning projects in multiple domains, including in regression-based tasks such as taxi fare prediction in New York City, image classification of cats and dogs using a convolutional neural network, implementing a facial recognition security system using Siamese Neural Networks, and more.
Feb 2019 10 hours 16 minutes
Advanced Deep Learning with TensorFlow 2 and Keras
Advanced Deep Learning with TensorFlow 2 and Keras
A second edition of the bestselling guide to exploring and mastering deep learning with Keras, updated to include TensorFlow 2.x with new chapters on object detection, semantic segmentation, and unsupervised learning using mutual information.
Feb 2020 17 hours 4 minutes
Advanced Deep Learning with R
Advanced Deep Learning with R
This book will help readers to apply deep learning algorithms in R using advanced examples. You will cover variants of neural network models such as ANN, CNN, RNN, LSTM, and more using expert techniques. Readers will make use of popular deep learning libraries such as Keras-R, Tensorflow-R, and more to implement AI models.
Dec 2019 11 hours 44 minutes
Advanced Deep Learning with Keras
Advanced Deep Learning with Keras
This book covers advanced deep learning techniques to create successful AI. Using MLPs, CNNs, and RNNs as building blocks to more advanced techniques, you’ll study deep neural network architectures, Autoencoders, Generative Adversarial Networks (GANs), Variational AutoEncoders (VAEs), and Deep Reinforcement Learning (DRL) critical to many cutting-edge AI results.
Oct 2018 12 hours 16 minutes
Deep Learning with Keras
Deep Learning with Keras
Keras is a high-level neural network library written in Python that runs on top of either Theano or TensorFlow. With this book, you’ll learn the basics of Keras in a highly practical way and understand how this minimal, highly modular framework runs on both CPU and GPU, allowing you to put your ideas into action in the shortest possible time.
Apr 2017 10 hours 36 minutes
Hands-On Computer Vision with TensorFlow 2
Hands-On Computer Vision with TensorFlow 2
Computer vision is achieving a new frontier of capabilities in fields like health, automobile or robotics. This book explores TensorFlow 2, Google's open-source AI framework, and teaches how to leverage deep neural networks for visual tasks. It will help you acquire the insight and skills to be a part of the exciting advances in computer vision.
May 2019 12 hours 24 minutes
Right arrow icon

Personalised recommendations for you

Based on your interests and search pattern
Left arrow icon
Et al.
Et al.
Ever wonder why speech recognition systems don't understand the Scottish accent, or what would happen if an astronaut only ate mac 'n' cheese, or other spurious reflections you'd have at a bar? We did, then collated those deliberations into absurd research articles with fake figures and methodologies inspired by even more fictionally absurd studies.
Aug 2023 7 hours 40 minutes
Generative AI with LangChain
Generative AI with LangChain
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
Generative AI with LangChain
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
Generative AI with LangChain
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
Generative AI with LangChain
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Dec 2023 12 hours 0 minutes
Mastering Tableau 2023
Mastering Tableau 2023
This book is a comprehensive resource to mastering your Tableau skills and becoming a BI expert. As you progress, you will learn how to build advanced dashboards and improve your storytelling to derive key business insight, as well as make you well-versed with advanced functionalities of Tableau in the business intelligence domain.
Aug 2023 22 hours 48 minutes
Building AI Applications with ChatGPT APIs
Building AI Applications with ChatGPT APIs
This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.
Sep 2023 8 hours 36 minutes
Building AI Applications with ChatGPT APIs
Building AI Applications with ChatGPT APIs
This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.
Sep 2023 8 hours 36 minutes
Data Engineering with AWS
Data Engineering with AWS
Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.
Oct 2023 21 hours 12 minutes
Modern Data Architecture on AWS
Modern Data Architecture on AWS
Every organization wants an agile, performant, and cost-effective data platform that meets all their current and future business needs. Purpose-built AWS analytics services and their features play a big part in building such a modern data platform. This book brings to you all the design and architectural patterns that’ll help you achieve this goal.
Aug 2023 14 hours 0 minutes
Practical Guide to Applied Conformal Prediction in Python
Practical Guide to Applied Conformal Prediction in Python
Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.
Dec 2023 8 hours 0 minutes
TinyML Cookbook
TinyML Cookbook
With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. It provides a comprehensive understanding of the theoretical foundations while giving you hands-on experience training ML models for deployment on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano microcontrollers.
Nov 2023 22 hours 8 minutes
Right arrow icon