Manpreet Singh Ghotra's Books

Neural Network Programming with TensorFlow

Unleash the power of TensorFlow to train efficient neural networks

By: Manpreet Singh Ghotra,Rajdeep Dua

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Neural Network Programming with TensorFlow

Unleash the power of TensorFlow to train efficient neural networks

By: Manpreet Singh Ghotra,Rajdeep Dua

Neural Networks and their implementation decoded with TensorFlow About This Book Develop a strong background in neural network programming from scratch, using the popular Tensorflow library. Use Tensorflow to implement different kinds of neural networks – from simple feedforward neural networks to multilayered perceptrons, CNNs, RNNs and more. A highly practical guide including real-world datasets and use-cases to simplify your understanding of neural networks and their implementation. Who This Book Is For This book is meant for developers with a statistical background who want to work with neural networks. Though we will be using TensorFlow as the underlying library for neural networks, book can be used as a generic resource to bridge the gap between the math and the implementation of deep learning. If you have some understanding of Tensorflow and Python and want to learn what happens at a level lower than the plain API syntax, this book is for you. What You Will Learn Learn Linear Algebra and mathematics behind neural network. Dive deep into Neural networks from the basic to advanced concepts like CNN, RNN Deep Belief Networks, Deep Feedforward Networks. Explore Optimization techniques for solving problems like Local minima, Global minima, Saddle points Learn through real world examples like Sentiment Analysis. Train different types of generative models and explore autoencoders. Explore TensorFlow as an example of deep learning implementation. In Detail If you're aware of the buzz surrounding the terms such as "machine learning," "artificial intelligence," or "deep learning," you might know what neural networks are. Ever wondered how they help in solving complex computational problem efficiently, or how to train efficient neural networks? This book will teach you just that. You will start by getting a quick overview of the popular TensorFlow library and how it is used to train different neural networks. You will get a thorough understanding of the fundamentals and basic math for neural networks and why TensorFlow is a popular choice Then, you will proceed to implement a simple feed forward neural network. Next you will master optimization techniques and algorithms for neural networks using TensorFlow. Further, you will learn to implement some more complex types of neural networks such as convolutional neural networks, recurrent neural networks, and Deep Belief Networks. In the course of the book, you will be working on real-world datasets to get a hands-on understanding of neural network programming. You will also get to train generative models and will learn the applications of autoencoders. By the end of this book, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle. While you are learning about various neural network implementations you will learn the underlying mathematics and linear algebra and how they map to the appropriate TensorFlow constructs. Style and Approach This book is designed to give you just the right number of concepts to back up the examples. With real-world use cases and problems solved, this book is a handy guide for you. Each concept is backed by a generic and real-world problem, followed by a variation, making you independent and able to solve any problem with neural networks. All of the content is demystified by a simple and straightforward approach.

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266

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

1788397754

ISBN 13

9781788397759

Keras Deep Learning Cookbook

Over 30 recipes for implementing deep neural networks in Python

By: Rajdeep Dua,Manpreet Singh Ghotra

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Keras Deep Learning Cookbook

Over 30 recipes for implementing deep neural networks in Python

By: Rajdeep Dua,Manpreet Singh Ghotra

Leverage the power of deep learning and Keras to develop smarter and more efficient data models Key FeaturesUnderstand different neural networks and their implementation using KerasExplore recipes for training and fine-tuning your neural network modelsPut your deep learning knowledge to practice with real-world use-cases, tips, and tricksBook Description Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy. The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks. By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning What you will learnInstall and configure Keras in TensorFlowMaster neural network programming using the Keras library Understand the different Keras layers Use Keras to implement simple feed-forward neural networks, CNNs and RNNsWork with various datasets and models used for image and text classificationDevelop text summarization and reinforcement learning models using KerasWho this book is for Keras Deep Learning Cookbook is for you if you are a data scientist or machine learning expert who wants to find practical solutions to common problems encountered while training deep learning models. A basic understanding of Python and some experience in machine learning and neural networks is required for this book.

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244

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Packt Publishing Ltd

Published Date

ISBN 10

1788623088

ISBN 13

9781788623087

Machine Learning with Spark

By: Rajdeep Dua,Manpreet Singh Ghotra,Nick Pentreath

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Machine Learning with Spark

By: Rajdeep Dua,Manpreet Singh Ghotra,Nick Pentreath

Create scalable machine learning applications to power a modern data-driven business using Spark 2.x About This Book Get to the grips with the latest version of Apache Spark Utilize Spark's machine learning library to implement predictive analytics Leverage Spark's powerful tools to load, analyze, clean, and transform your data Who This Book Is For If you have a basic knowledge of machine learning and want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and Python languages. What You Will Learn Get hands-on with the latest version of Spark ML Create your first Spark program with Scala and Python Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2 Access public machine learning datasets and use Spark to load, process, clean, and transform data Use Spark's machine learning library to implement programs by utilizing well-known machine learning models Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models Write Spark functions to evaluate the performance of your machine learning models In Detail This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business. Style and approach This practical tutorial with real-world use cases enables you to develop your own machine learning systems with Spark. The examples will help you combine various techniques and models into an intelligent machine learning system.

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523

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Packt Publishing Ltd

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ISBN 10

1785886428

ISBN 13

9781785886423

Machine Learning with Spark

By: Rajdeep Dua,Manpreet Singh Ghotra,Nick Pentreath

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Machine Learning with Spark

By: Rajdeep Dua,Manpreet Singh Ghotra,Nick Pentreath

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Solve jigsaw puzzle

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523

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

1785886428

ISBN 13

9781785886423

Keras Deep Learning Cookbook

Over 30 recipes for implementing deep neural networks in Python

By: Rajdeep Dua,Manpreet Singh Ghotra

Write a review Read reviews Take a Quiz Solve Book Puzzle

Keras Deep Learning Cookbook

Over 30 recipes for implementing deep neural networks in Python

By: Rajdeep Dua,Manpreet Singh Ghotra

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N/A

Write a review

Solve jigsaw puzzle

Age

Page Count

244

Publisher

Packt Publishing Ltd

Published Date

ISBN 10

1788623088

ISBN 13

9781788623087

Book's by Manpreet Singh Ghotra

Neural Network Programming with TensorFlow

Neural Network Programming with TensorFlow

Keras Deep Learning Cookbook

Keras Deep Learning Cookbook

Machine Learning with Spark

Machine Learning with Spark

Machine Learning with Spark

Machine Learning with Spark

Keras Deep Learning Cookbook

Keras Deep Learning Cookbook

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