Python Deep Learning Develop Your First Neural Network in Python Using Tensorflow Keras and Pytorch

Written By Samuel Burns
Python Deep Learning  Develop Your First Neural Network in Python Using Tensorflow  Keras  and Pytorch
  • Publsiher : Step-By-Step Tutorial for Begi
  • Release : 03 April 2019
  • ISBN : 9781092562225
  • Pages : 172 pages
  • Rating : /5 from reviews
GET THIS BOOKPython Deep Learning Develop Your First Neural Network in Python Using Tensorflow Keras and Pytorch


Download or read book entitled Python Deep Learning Develop Your First Neural Network in Python Using Tensorflow Keras and Pytorch by author: Samuel Burns which was release on 03 April 2019 and published by Step-By-Step Tutorial for Begi with total page 172 pages . This book available in PDF, EPUB and Kindle Format. Build your Own Neural Network today. Through easy-to-follow instruction and examples, you'll learn the fundamentals of Deep learning and build your very own Neural Network in Python using TensorFlow, Keras, PyTorch, and Theano. While you have the option of spending thousands of dollars on big and boring textbooks, we recommend getting the same pieces of information for a fraction of the cost. So Get Your Copy Now!! Why this book? Book ObjectivesThe following are the objectives of this book: To help you understand deep learning in detail To help you know how to get started with deep learning in Python by setting up the coding environment. To help you transition from a deep learning Beginner to a Professional. To help you learn how to develop a complete and functional artificial neural network model in Python on your own. Who this Book is for? The author targets the following groups of people: Anybody who is a complete beginner to deep learning with Python. Anybody in need of advancing their Python for deep learning skills. Professors, lecturers or tutors who are looking to find better ways to explain Deep Learning to their students in the simplest and easiest way. Students and academicians, especially those focusing on python programming, neural networks, machine learning, and deep learning. What do you need for this Book? You are required to have installed the following on your computer: Python 3.X. TensorFlow . Keras . PyTorch The Author guides you on how to install the rest of the Python libraries that are required for deep learning.The author will guide you on how to install and configure the rest. What is inside the book? What is Deep Learning? An Overview of Artificial Neural Networks. Exploring the Libraries. Installation and Setup. TensorFlow Basics. Deep Learning with TensorFlow. Keras Basics. PyTorch Basics. Creating Convolutional Neural Networks with PyTorch. Creating Recurrent Neural Networks with PyTorch. From the back cover. Deep learning is part of machine learning methods based on learning data representations. This book written by Samuel Burns provides an excellent introduction to deep learning methods for computer vision applications. The author does not focus on too much math since this guide is designed for developers who are beginners in the field of deep learning. The book has been grouped into chapters, with each chapter exploring a different feature of the deep learning libraries that can be used in Python programming language. Each chapter features a unique Neural Network architecture including Convolutional Neural Networks. After reading this book, you will be able to build your own Neural Networks using Tenserflow, Keras, and PyTorch. Moreover, the author has provided Python codes, each code performing a different task. Corresponding explanations have also been provided alongside each piece of code to help the reader understand the meaning of the various lines of the code. In addition to this, screenshots showing the output that each code should return have been given. The author has used a simple language to make it easy even for beginners to understand.

Python Deep Learning Develop Your First Neural Network in Python Using Tensorflow Keras and Pytorch

Python Deep Learning  Develop Your First Neural Network in Python Using Tensorflow  Keras  and Pytorch
  • Author : Samuel Burns
  • Publisher : Step-By-Step Tutorial for Begi
  • Release Date : 2019-04-03
  • Total pages : 172
  • ISBN : 9781092562225
GET BOOK

Summary : Build your Own Neural Network today. Through easy-to-follow instruction and examples, you'll learn the fundamentals of Deep learning and build your very own Neural Network in Python using TensorFlow, Keras, PyTorch, and Theano. While you have the option of spending thousands of dollars on big and boring textbooks, we recommend ...

Introduction to Deep Learning and Neural Networks with PythonTM

Introduction to Deep Learning and Neural Networks with PythonTM
  • Author : Ahmed Fawzy Gad,Fatima Ezzahra Jarmouni
  • Publisher : Academic Press
  • Release Date : 2020-12-07
  • Total pages : 300
  • ISBN : 9781092562225
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Summary : Introduction to Deep Learning and Neural Networks with PythonTM: A Practical Guide is an intensive step-by-step guide for neuroscientists to fully understand, practice, and build neural networks. Providing math and PythonTM code examples to clarify neural network calculations, by book’s end readers will fully understand how neural networks work ...

Introduction to Deep Learning

Introduction to Deep Learning
  • Author : Sandro Skansi
  • Publisher : Springer
  • Release Date : 2018-02-04
  • Total pages : 191
  • ISBN : 9781092562225
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Summary : This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content ...

Introduction to Deep Learning

Introduction to Deep Learning
  • Author : Juergen Brauer
  • Publisher : Createspace Independent Publishing Platform
  • Release Date : 2018-08-03
  • Total pages : 246
  • ISBN : 9781092562225
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Summary : About the book: In Computer Sciences there is currently a gold rush mood due to a new field called "Deep Learning".But what is Deep Learning? This book is an introduction to Neural Networks and the most important Deep Learning model - the Convolutional Neural Network model including a description ...

Deep Learning with Python

Deep Learning with Python
  • Author : Chao Pan
  • Publisher : Createspace Independent Publishing Platform
  • Release Date : 2016-06-14
  • Total pages : 124
  • ISBN : 9781092562225
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Summary : ***** BUY NOW (will soon return to 24.77 $) *****Are you thinking of learning deep Learning using Python? (For Beginners Only) If you are looking for a beginners guide to learn deep learning, in just a few hours, this book is for you. From AI Sciences Publisher Our books may be the best ...

Deep Learning Fundamentals

Deep Learning Fundamentals
  • Author : Chao Pan
  • Publisher : Createspace Independent Publishing Platform
  • Release Date : 2016-06-15
  • Total pages : 96
  • ISBN : 9781092562225
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Summary : This book is the first part of the book deep learning with Python write by the same author. If you already purchased deep learning with Python by Chao Pan no need for this book. Are you thinking of learning deep Learning fundamentals, concepts and algorithms? (For Beginners) If you are ...

Mastering Deep Learning Fundamentals

Mastering Deep Learning Fundamentals
  • Author : Ai Publishing
  • Publisher : AI Publishing
  • Release Date : 2019-06-09
  • Total pages : 162
  • ISBN : 9781092562225
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Summary : ** ONE HOUR FREE VIDEO COURSE IN DEEP LEARNING INCLUDED** **Get your copy now, the price will change soon**You are interested in deep learning, but don't know how to get startedLet us help youWho are the book for? Are a college student and want more than your university course offers ...

Deep Learning with PyTorch Quick Start Guide

Deep Learning with PyTorch Quick Start Guide
  • Author : David Julian
  • Publisher : Packt Publishing Ltd
  • Release Date : 2018-12-24
  • Total pages : 158
  • ISBN : 9781092562225
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Summary : Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing. Key Features Clear and concise explanations Gives important insights into deep learning models Practical demonstration of key concepts Book Description ...

Deep Learning with PyTorch

Deep Learning with PyTorch
  • Author : Eli Stevens,Luca Antiga,Thomas Viehmann
  • Publisher : Manning Publications
  • Release Date : 2020-08-04
  • Total pages : 520
  • ISBN : 9781092562225
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Summary : Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with ...

Mastering Deep Learning Fundamentals with Python

Mastering Deep Learning Fundamentals with Python
  • Author : Richard Wilson
  • Publisher : Independently Published
  • Release Date : 2019-07-14
  • Total pages : 220
  • ISBN : 9781092562225
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Summary : ★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★ Step into the fascinating world of data science.. You to participate in the revolution that brings artificial intelligence back to the heart of our society, thanks to data scientists. Data science consists in translating problems ...

Introduction to Deep Learning for Engineers

Introduction to Deep Learning for Engineers
  • Author : Tariq M. Arif
  • Publisher : Morgan & Claypool Publishers
  • Release Date : 2020-07-22
  • Total pages : 109
  • ISBN : 9781092562225
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Summary : This book provides a short introduction and easy-to-follow implementation steps of deep learning using Google Cloud Platform. It also includes a practical case study that highlights the utilization of Python and related libraries for running a pre-trained deep learning model. In recent years, deep learning-based modeling approaches have been used ...

Introduction to Deep Learning Using PyTorch

Introduction to Deep Learning Using PyTorch
  • Author : Goku Mohandas
  • Publisher : Unknown
  • Release Date : 2018
  • Total pages : 212
  • ISBN : 9781092562225
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Summary : "This video will serve as an introduction to PyTorch, a dynamic, deep learning framework in Python. In this video, you will learn to create simple neural networks, which are the backbone of artificial intelligence. We will start with fundamental concepts of deep learning (including feed forward networks, back-propagation, loss functions, ...

Practical Deep Learning

Practical Deep Learning
  • Author : Ron Kneusel
  • Publisher : No Starch Press
  • Release Date : 2021-03-16
  • Total pages : 464
  • ISBN : 9781092562225
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Summary : Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you’ve been curious about machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the ...

Introduction to Deep Learning and Neural Networks with PythonT

Introduction to Deep Learning and Neural Networks with PythonT
  • Author : Ahmed Fawzy Gad,Fatima Ezzahra Jarmouni
  • Publisher : Academic Press
  • Release Date : 2020-12-10
  • Total pages : 300
  • ISBN : 9781092562225
GET BOOK

Summary : Introduction to Deep Learning and Neural Networks with PythonT: A Practical Guide is an intensive step-by-step guide for neuroscientists to fully understand, practice, and build neural networks. Providing math and PythonT code examples to clarify neural network calculations, by book's end readers will fully understand how neural networks work starting ...

A Practical Approach for Machine Learning and Deep Learning Algorithms

A Practical Approach for Machine Learning and Deep Learning Algorithms
  • Author : Abhishek Kumar Pandey,Pramod Singh Rathore,Dr. S. Balamurugan
  • Publisher : BPB Publications
  • Release Date : 2019-09-18
  • Total pages : 280
  • ISBN : 9781092562225
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Summary : Guide covering topics from machine learning, regression models, neural network to tensor flow DESCRIPTION Machine learning is mostly sought in the research field and has become an integral part of many research projects nowadays including commercial applications, as well as academic research. Application of machine learning ranges from finding friends ...