Pragmatic Deep Learning For Dummies

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Pragmatic Deep Learning For Dummies

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Author : Benjamin Young
language : en
Publisher:
Release Date : 2019-02-14

Pragmatic Deep Learning For Dummies written by Benjamin Young and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-14 with Computers categories.

Summary This book will help you learn and grasp deep learning technology from ground zero with many interesting real world examples. It could also be used as a quick guide on how to use and understand deep learning in the real life. Description AI especially Deep Learning has made tremendous progress in recent years. It start to spread to all industries. Quote from Andrew Ng, a famous AI researcher: "AI is the new electricity. About 100 years ago, electricity transformed every major industry. AI has advanced to the point where it has the power to transform every major sector in coming years." Unless you are a refresh graduated student with AI/deep learning major, many of us do not have a formal machine learning/deep learning training before, so it is time to keep updated with latest technology. This book will help you learn and grasp deep learning technology from ground zero with many interesting real world examples using python/keras. The books could also be used as a quick guide on how to use and understand deep learning in the real life. Readers should have basic knowledge of python, scripting etc. Free lifetime upgrade for later editions ( as an electronic copy ). Please contact author for this. Table of Contents Introduction What is deep learning Deep neural network basic conectps Python and NumPy basic Deep learning development environments MNIST CNN example: A deep dive of how to handle image data Pre-trained model, transfer learning and fine-tuning Recurrent neural network - how to handle sequences data Natural Langauge Processing Optical character recogniztion Audio processing, speech processing Autoencoder network Deep reinforcement learning Learning from scratch (self-play) AlphaZero How to deploy deep learning model.

Deep Learning Reinforcement Learning And The Rise Of Intelligent Systems

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Author : Uddin, M. Irfan
language : en
Publisher: IGI Global
Release Date : 2024-02-26

Deep Learning Reinforcement Learning And The Rise Of Intelligent Systems written by Uddin, M. Irfan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-26 with Computers categories.

The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields. Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals.

Natural Language Processing For Beginners

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Author : Dr. Sumalatha Lingamgunta
language : en
Publisher: Academic Guru Publishing House
Release Date : 2025-01-06

Natural Language Processing For Beginners written by Dr. Sumalatha Lingamgunta and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-06 with Study Aids categories.

Natural Language Processing for Beginners serves as an introduction to the essential principles and tools used to understand and manipulate human language through machines. Written specifically for beginners, this book focuses on making the complex world of NLP accessible by breaking down concepts into simple, easy-to-follow explanations. The book covers key topics such as text preprocessing, tokenization, sentiment analysis, named entity recognition, and word embeddings, offering a comprehensive overview of the field’s core areas. Structured in a way that facilitates learning by doing, the book provides practical exercises, code examples, and hands-on projects that guide readers step-by-step. It introduces the key libraries and tools like NLTK, spaCy, and Hugging Face Transformers, ensuring readers become familiar with industry-standard resources. The book also explores applications of NLP in real-world scenarios, such as chatbots, social media monitoring, and document classification. Designed for aspiring data scientists, software engineers, and anyone interested in language technology, Natural Language Processing for Beginners is the ideal entry point for those looking to master NLP techniques. Whether you aim to build intelligent systems or dive deeper into the field of AI, this book lays the foundation for an exciting journey into the world of language understanding.

R Machine Learning By Example

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Author : Raghav Bali
language : en
Publisher:
Release Date : 2016

R Machine Learning By Example written by Raghav Bali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Computers categories.

Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfullyAbout This Book* Get to grips with the concepts of machine learning through exciting real-world examples* Visualize and solve complex problems by using power-packed R constructs and its robust packages for machine learning* Learn to build your own machine learning system with this example-based practical guideWho This Book Is ForIf you are interested in mining useful information from data using state-of-the-art techniques to make data-driven decisions, this is a go-to guide for you. No prior experience with data science is required, although basic knowledge of R is highly desirable. Prior knowledge in machine learning would be helpful but is not necessary.What You Will Learn* Utilize the power of R to handle data extraction, manipulation, and exploration techniques* Use R to visualize data spread across multiple dimensions and extract useful features* Explore the underlying mathematical and logical concepts that drive machine learning algorithms* Dive deep into the world of analytics to predict situations correctly* Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action* Write reusable code and build complete machine learning systems from the ground up* Solve interesting real-world problems using machine learning and R as the journey unfolds* Harness the power of robust and optimized R packages to work on projects that solve real-world problems in machine learning and data scienceIn DetailData science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems.This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems.You'll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of machine learning, following current trends and cover major algorithms as well as popular R packages in detail. These projects have been neatly divided into six different chapters covering the worlds of e-commerce, finance, and social-media, which are at the very core of this data-driven revolution. Each of the projects will help you to understand, explore, visualize, and derive insights depending upon the domain and algorithms.Through this book, you will learn to apply the concepts of machine learning to deal with data-related problems and solve them using the powerful yet simple language, R.Style and approachThe book is an enticing journey that starts from the very basics to gradually pick up pace as the story unfolds. Each concept is first defined in the larger context of things succinctly, followed by a detailed explanation of their application. Each topic is explained with the help of a project that solves a real real-world problem involving hands-on work thus giving you a deep insight into the world of machine learning.

Machine Learning Ecml 98

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Author : Claire Nedellec
language : en
Publisher: Lecture Notes in Artificial Intelligence
Release Date : 1998-04-08

Machine Learning Ecml 98 written by Claire Nedellec and has been published by Lecture Notes in Artificial Intelligence this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-04-08 with Computers categories.

This book constitutes the refereed proceedings of the 10th European Conference on Machine Learning, ECML-98, held in Chemnitz, Germany, in April 1998. The book presents 21 revised full papers and 25 short papers reporting on work in progress together with two invited contributions; the papers were selected from a total of 100 submissions. The book is divided in sections on applications of ML, Bayesian networks, feature selection, decision trees, support vector learning, multiple models for classification, inductive logic programming, relational learning, instance-based learning, clustering, genetic algorithms, reinforcement learning and neural networks.

Machine Learning Ecml

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Author :
language : en
Publisher:
Release Date : 1998

Machine Learning Ecml written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Induction (Logic) categories.

Proceedings Of The Fifth International Conference On Machine Learning

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Author : John Laird
language : en
Publisher: Morgan Kaufmann Publishers
Release Date : 1988

Proceedings Of The Fifth International Conference On Machine Learning written by John Laird and has been published by Morgan Kaufmann Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computers categories.

Machine Learning Proceedings 1988.

Proceedings Of The International Workshop On Machine Learning

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Author :
language : en
Publisher:
Release Date : 1985

Proceedings Of The International Workshop On Machine Learning written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Artificial intelligence categories.

The Routledge Pragmatics Encyclopedia

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Author : Louise Cummings
language : en
Publisher:
Release Date : 2013

The Routledge Pragmatics Encyclopedia written by Louise Cummings and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Foreign Language Study categories.

This is a comprehensive reference volume that will give the reader an insight into all the concepts, theories, issues and scholars that have shaped the field of pragmatics.

Teaching For Quality Learning At University

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Author : John Burville Biggs
language : en
Publisher: Open University Press
Release Date : 2003

Teaching For Quality Learning At University written by John Burville Biggs and has been published by Open University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Education categories.

John Biggs tackles how academics can improve their teaching in today's circumstances or large classes and diverse student populations. He discusses areas such as making the large lecture a more exciting and productive learning experience.