0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Hands-On Deep Learning with TensorFlow

You're reading from Hands-On Deep Learning with TensorFlow Uncover what is underneath your data!

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781787282773

Length 174 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Deep Learning

Author (1):

Dan Van Boxel

View More author details

Table of Contents (7) Chapters

Preface

1. Getting Started

2. Deep Neural Networks FREE CHAPTER

3. Convolutional Neural Networks

4. Introducing Recurrent Neural Networks

5. Wrapping Up

Index

The future of TensorFlow

In this section, we will observe how TensorFlow is changing, who is starting to use TensorFlow, and how you can make an impact contributing to it.

Since it was released in late 2015, TensorFlow has already seen several more releases:

The future of TensorFlow

TensorFlow is constantly being updated. Although it isn't an official Google product, it is also open source and hosted on GitHub. At the time of writing, TensorFlow is at release 1.2. The most recent release added distributed computing capabilities. These are beyond the scope of this book, but generally speaking, they allow computation across multiple GPUs on multiple machines for maximum parallelization. Under heavy development, more features are always just around the corner. TensorFlow is becoming more popular every day.

Several software companies have released machine learning frameworks recently, but TensorFlow stands out in adoption. Internally, Google is practicing what they preach. Their acclaimed DeepMind team has switched...

The rest of the chapter is locked

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.

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 €18.99/month. Cancel anytime

Authors (1)

Dan Van Boxel

Dan Van Boxel

Dan Van Boxel is a data scientist and machine learning engineer with over 10 years of experience. He is most well-known for Dan Does Data, a YouTube livestream demonstrating the power and pitfalls of neural networks. He has developed and applied novel statistical models of machine learning to topics such as accounting for truck traffic on highways, travel time outlier detection, and other areas. Dan has also published research articles and presented findings at the Transportation Research Board and other academic journals.

See other products by Dan Van Boxel

Other recommended products

Related to this chapter

Hands-On Java Deep Learning for Computer Vision

Hands-On Java Deep Learning for Computer Vision

This book will take you through the process of efficiently training deep neural networks in Java for Computer Vision-related tasks. You will build real-world applications ranging from simple Java handwritten digit recognition models to real-time autonomous car driving systems and face recognition models using the popular Java-based libraries.

Feb 2019 8h 40m

Recurrent Neural Networks with Python Quick Start Guide

Recurrent Neural Networks with Python Quick Start Guide

Developers struggle to find an easy to follow learning resource for implementing Recurrent Neural Network(RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve the results. This book will teach you the fundamentals of RNNs with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling.

Recurrent Neural Networks with Python Quick Start Guide

Recurrent Neural Networks with Python Quick Start Guide

Developers struggle to find an easy to follow learning resource for implementing Recurrent Neural Network(RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve the results. This book will teach you the fundamentals of RNNs with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling.

Recurrent Neural Networks with Python Quick Start Guide

Recurrent Neural Networks with Python Quick Start Guide

Developers struggle to find an easy to follow learning resource for implementing Recurrent Neural Network(RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve the results. This book will teach you the fundamentals of RNNs with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling.

Recurrent Neural Networks with Python Quick Start Guide

Recurrent Neural Networks with Python Quick Start Guide

Developers struggle to find an easy to follow learning resource for implementing Recurrent Neural Network(RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve the results. This book will teach you the fundamentals of RNNs with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling.

Hands-On Deep Learning for Images with TensorFlow

Hands-On Deep Learning for Images with TensorFlow

In this book, you will come across various real-world projects which will teach you how to leverage Tensforflow's capabilities to perform efficient image processing tasks. By the end of this book, you will have mastered all the concepts of deep learning for Images and their implementations with Tensorflow and Keras

Jul 2018 3h 12m

Hands-On Deep Learning for Images with TensorFlow

Hands-On Deep Learning for Images with TensorFlow

In this book, you will come across various real-world projects which will teach you how to leverage Tensforflow's capabilities to perform efficient image processing tasks. By the end of this book, you will have mastered all the concepts of deep learning for Images and their implementations with Tensorflow and Keras

Jul 2018 3h 12m

Practical Time Series Analysis

Practical Time Series Analysis

Practical Time Series Analysis will introduce you to the basic concepts of time series analysis and describe powerful yet simple techniques in Python which data scientists and data engineers would find useful in dealing with real life datasets in industrial settings. This book focuses on explaining important concepts and practical techniques to process, summarize and model time series data. Real life case studies with code snippets in Python are used to demonstrate the concepts and techniques.

Practical Time Series Analysis

Practical Time Series Analysis

Practical Time Series Analysis will introduce you to the basic concepts of time series analysis and describe powerful yet simple techniques in Python which data scientists and data engineers would find useful in dealing with real life datasets in industrial settings. This book focuses on explaining important concepts and practical techniques to process, summarize and model time series data. Real life case studies with code snippets in Python are used to demonstrate the concepts and techniques.

Practical Time Series Analysis

Practical Time Series Analysis

Practical Time Series Analysis will introduce you to the basic concepts of time series analysis and describe powerful yet simple techniques in Python which data scientists and data engineers would find useful in dealing with real life datasets in industrial settings. This book focuses on explaining important concepts and practical techniques to process, summarize and model time series data. Real life case studies with code snippets in Python are used to demonstrate the concepts and techniques.

Practical Time Series Analysis

Practical Time Series Analysis

Practical Time Series Analysis will introduce you to the basic concepts of time series analysis and describe powerful yet simple techniques in Python which data scientists and data engineers would find useful in dealing with real life datasets in industrial settings. This book focuses on explaining important concepts and practical techniques to process, summarize and model time series data. Real life case studies with code snippets in Python are used to demonstrate the concepts and techniques.

Practical Time Series Analysis

Practical Time Series Analysis

Practical Time Series Analysis will introduce you to the basic concepts of time series analysis and describe powerful yet simple techniques in Python which data scientists and data engineers would find useful in dealing with real life datasets in industrial settings. This book focuses on explaining important concepts and practical techniques to process, summarize and model time series data. Real life case studies with code snippets in Python are used to demonstrate the concepts and techniques.

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.