Python Programming Deep Learning
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Deep Learning With Python
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Author : Francois Chollet
language : en
Publisher: Simon and Schuster
Release Date : 2017-11-30
Deep Learning With Python written by Francois Chollet and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-30 with Computers categories.
Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance
Deep Learning For Coders With Fastai And Pytorch
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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29
Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Machine Learning Algorithms Using Python Programming
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Author : Gopal Sakarkar
language : en
Publisher: Nova Science Publishers
Release Date : 2021
Machine Learning Algorithms Using Python Programming written by Gopal Sakarkar and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Computers categories.
"The machine learning field is concerned with the question of how to create computer programs that automatically improve information. In recent years, many successful electronic learning applications have been made, from data mining systems that learn to detect fraudulent credit card transactions, filtering programs that learn user readings, to private cars that learn to drive on public highways. At the same time, there have been significant developments in the concepts and algorithms that form the basis for this field. Machine learning is programming computers to optimize a performance criterion using example data or past experience. The goal of this textbook is to present the key concepts of Machine Learning which includes Python concepts and Interpreter, Foundation of Machine Learning, Data Pre-processing, Supervised Machine Learning, Unsupervised Machine Learning, Reinforcement Learning, Kernel Machine, Design and analysis of Machine Learning experiment and Data visualization. The theoretical concepts along with coding implementation are covered. This book aims to pursue a middle ground between a theoretical textbook and one that focuses on applications. The book concentrates on the important ideas in machine learning"--
Deep Learning Crash Course For Beginners With Python
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Author : Ai Publishing
language : en
Publisher:
Release Date : 2020-05-25
Deep Learning Crash Course For Beginners With Python written by Ai Publishing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-25 with categories.
Artificial intelligence is the rage today! While you may find it difficult to understand the most recent advancements in AI, it simply boils down to two most celebrated developments: Machine Learning and Deep Learning. In 2020, Deep Learning is leagues ahead because of its supremacy when it comes to accuracy, especially when trained with enormous amounts of data. Deep Learning, essentially, is a subset of Machine Learning, but it's capable of achieving tremendous power and flexibility. And the era of big data technology presents vast opportunities for incredible innovations in deep learning. How Is This Book Different? This book gives equal importance to the theoretical as well as practical aspects of deep learning. You will understand how high-performing deep learning algorithms work. In every chapter, the theoretical explanation of the different types of deep learning techniques is followed by practical examples. You will learn how to implement different deep learning techniques using the TensorFlow Keras library for Python. Each chapter contains exercises that you can use to assess your understanding of the concepts explained in that chapter. Also, in the Resources, the Python notebook for each chapter is provided. The key advantage of buying this book is you get instant access to all the extra content presented with this book--Python codes, references, exercises, and PDFs--on the publisher's website. You don't need to spend an extra cent. The datasets used in this book are either downloaded at runtime or are available in the Resources/Datasets folder. Another advantage is a detailed explanation of the installation steps for the software that you will need to implement the various deep learning algorithms in this book is provided. That is, you get to experiment with the practical aspects of Deep Learning right from page 1. Even if you are new to Python, you will find the crash course on Python programming language in the first chapter immensely useful. Since all the codes and datasets are included with this book, you only need access to a computer with the internet to get started. The topics covered include: Python Crash Course Deep Learning Prerequisites: Linear and Logistic Regression Neural Networks from Scratch in Python Introduction to TensorFlow and Keras Convolutional Neural Networks Sequence Classification with Recurrent Neural Networks Deep Learning for Natural Language Processing Unsupervised Learning with Autoencoders Answers to All Exercises Click the BUY button and download the book now to start your Deep Learning journey.
Deep Learning With Python
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Author : Nikhil Ketkar
language : en
Publisher: Apress
Release Date : 2017-04-18
Deep Learning With Python written by Nikhil Ketkar and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-18 with Computers categories.
Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often acquired by practitioners by reading source code, manuals, and posting questions on community forums, which tends to be a slow and a painful process. Deep Learning with Python allows you to ramp up to such practical know-how in a short period of time and focus more on the domain, models, and algorithms. This book briefly covers the mathematical prerequisites and fundamentals of deep learning, making this book a good starting point for software developers who want to get started in deep learning. A brief survey of deep learning architectures is also included. Deep Learning with Python alsointroduces you to key concepts of automatic differentiation and GPU computation which, while not central to deep learning, are critical when it comes to conducting large scale experiments. What You Will Learn Leverage deep learning frameworks in Python namely, Keras, Theano, and Caffe Gain the fundamentals of deep learning with mathematical prerequisites Discover the practical considerations of large scale experiments Take deep learning models to production Who This Book Is For Software developers who want to try out deep learning as a practical solution to a particular problem. Software developers in a data science team who want to take deep learning models developed by data scientists to production.
Machine Learning And Deep Learning Using Python And Tensorflow
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Author : Venkata Reddy Konasani
language : en
Publisher: McGraw Hill Professional
Release Date : 2021-04-29
Machine Learning And Deep Learning Using Python And Tensorflow written by Venkata Reddy Konasani and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Technology & Engineering categories.
Understand the principles and practices of machine learning and deep learning This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in today’s smart devices and apps. You will get download links for datasets, code, and sample projects referred to in the text. Coverage includes: Machine learning and deep learning concepts Python programming and statistics fundamentals Regression and logistic regression Decision trees Model selection and cross-validation Cluster analysis Random forests and boosting Artificial neural networks TensorFlow and Keras Deep learning hyperparameters Convolutional neural networks Recurrent neural networks and long short-term memory
Artificial Intelligence With Python
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Author : Prateek Joshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-01-27
Artificial Intelligence With Python written by Prateek Joshi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with Computers categories.
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
Mastering Deep Learning Fundamentals With Python
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Author : Richard Wilson
language : en
Publisher: Independently Published
Release Date : 2019-07-14
Mastering Deep Learning Fundamentals With Python written by Richard Wilson and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-14 with categories.
★★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 of any other nature into quantitative modeling problems, solved by processing algorithms. This book, designed for anyone wishing to learn Deep Learning. This book presents the main techniques: deep neural networks, able to model all kinds of data, convolution networks, able to classify images, segment them and discover the objects or people who are there, recurring networks, it contains sample code so that the reader can easily test and run the programs. On the program: Deep learning Neural Networks and Deep Learning Deep Learning Parameters and Hyper-parameters Deep Neural Networks Layers Deep Learning Activation Functions Convolutional Neural Network Python Data Structures Best practices in Python and Zen of Python Installing Python Python These are some of the topics covered in this book: fundamentals of deep learning fundamentals of probability fundamentals of statistics fundamentals of linear algebra introduction to machine learning and deep learning fundamentals of machine learning fundamentals of neural networks and deep learning deep learning parameters and hyper-parameters deep neural networks layers deep learning activation functions convolutional neural network Deep learning in practice (in jupyter notebooks) python data structures best practices in python and zen of python installing python The 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. And more Get this book now to learn more about -- Deep learning in Python by setting up the coding environment.!
Python Machine Learning For Beginners
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Author : Finn Sanders
language : en
Publisher: Roland Bind
Release Date : 2019-05-22
Python Machine Learning For Beginners written by Finn Sanders and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-22 with Computers categories.
Imagine a world where you can make a computer program learn for itself? What if it could recognize who is in a picture or the exact websites that you want to look for when you type it into the program? What if you were able to create any kind of program that you wanted, even as a beginner programmer, without all of the convoluted codes and other information that makes your head spin? This is actually all possible. The programs that were mentioned before are all a part of machine learning. This is a breakthrough in the world of information technology, which allows the computer to learn how to behave, rather than asking the programmer to think of every single instance that may show up with their user ahead of time. it is taking over the world, and you may be using it now, without even realizing it. If you have used a search engine, worked with photo recognition, or done speech recognition devices on your phone, then you have worked with machine learning. And if you combine it with the Python programming language, it is faster, more powerful, and easier (even for beginners) to create your own programs today. Python is considered the ultimate coding language for beginners, but once you start to use it, you will never be able to tell. Many of the best programs out there use this language behind them, and if you are a beginner who is ready to learn, this is a great place to start. If you have a program in mind, or you just want to be able to get some programming knowledge and learn more about the power that comes behind it, then this is the guidebook for you. ★★Some of the topics that we will discuss include★★ ♦ The Fundamentals of Machine Learning, Deep learning, And Neural Networks ♦ How To Set Up Your Environment And Make Sure That Python, TensorFlow And Scikit-Learn Work Well For You ♦ How To Master Neural Network Implementation Using Different Libraries ♦ How Random Forest Algorithms Are Able To Help Out With Machine Learning ♦ How To Uncover Hidden Patterns And Structures With Clustering ♦ How Recurrent Neural Networks Work And When To Use ♦ The Importance Of Linear Classifiers And Why They Need To Be Used In Machine Learning ♦ And Much More! This guidebook is going to provide you with the information you need to get started with Python Machine Learning. If you have an idea for a great program, but you don't have the technical knowledge to make it happen, then this guidebook will help you get started. Machine learning has the capabilities, and Python has the ease, to help you, even as a beginner, create any product that you would like. If you want to learn more about how to make the best programs with Python Machine learning, buy the book today!
Python Deep Learning
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Author : Valentino Zocca
language : en
Publisher:
Release Date : 2017-04-28
Python Deep Learning written by Valentino Zocca and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-28 with Machine learning categories.
Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.About This Book* Explore and create intelligent systems using cutting-edge deep learning techniques* Implement deep learning algorithms and work with revolutionary libraries in Python* Get real-world examples and easy-to-follow tutorials on Theano, TensorFlow, H2O and moreWho This Book Is ForThis book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.What You Will Learn* Get a practical deep dive into deep learning algorithms* Explore deep learning further with Theano, Caffe, Keras, and TensorFlow* Learn about two of the most powerful techniques at the core of many practical deep learning implementations: Auto-Encoders and Restricted Boltzmann Machines* Dive into Deep Belief Nets and Deep Neural Networks* Discover more deep learning algorithms with Dropout and Convolutional Neural Networks* Get to know device strategies so you can use deep learning algorithms and libraries in the real worldIn DetailWith an increasing interest in AI around the world, deep learning has attracted a great deal of public attention. Every day, deep learning algorithms are used broadly across different industries.The book will give you all the practical information available on the subject, including the best practices, using real-world use cases. You will learn to recognize and extract information to increase predictive accuracy and optimize results.Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.Whether you want to dive deeper into Deep Learning, or want to investigate how to get more out of this powerful technology, you'll find everything inside.Style and approachPython Machine Learning by example follows practical hands on approach. It walks you through the key elements of Python and its powerful machine learning libraries with the help of real world projects.