Deep Learning For Beginners


Deep Learning For Beginners
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Deep Learning For Beginners


Deep Learning For Beginners
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Author : Dr. Pablo Rivas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-09-18

Deep Learning For Beginners written by Dr. Pablo Rivas 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 2020-09-18 with Computers categories.


Implement supervised, unsupervised, and generative deep learning (DL) models using Keras and Dopamine with TensorFlow Key FeaturesUnderstand the fundamental machine learning concepts useful in deep learningLearn the underlying mathematical concepts as you implement deep learning models from scratchExplore easy-to-understand examples and use cases that will help you build a solid foundation in DLBook Description With information on the web exponentially increasing, it has become more difficult than ever to navigate through everything to find reliable content that will help you get started with deep learning. This book is designed to help you if you're a beginner looking to work on deep learning and build deep learning models from scratch, and you already have the basic mathematical and programming knowledge required to get started. The book begins with a basic overview of machine learning, guiding you through setting up popular Python frameworks. You will also understand how to prepare data by cleaning and preprocessing it for deep learning, and gradually go on to explore neural networks. A dedicated section will give you insights into the working of neural networks by helping you get hands-on with training single and multiple layers of neurons. Later, you will cover popular neural network architectures such as CNNs, RNNs, AEs, VAEs, and GANs with the help of simple examples, and learn how to build models from scratch. At the end of each chapter, you will find a question and answer section to help you test what you've learned through the course of the book. By the end of this book, you'll be well-versed with deep learning concepts and have the knowledge you need to use specific algorithms with various tools for different tasks. What you will learnImplement recurrent neural networks (RNNs) and long short-term memory (LSTM) for image classification and natural language processing tasksExplore the role of convolutional neural networks (CNNs) in computer vision and signal processingDiscover the ethical implications of deep learning modelingUnderstand the mathematical terminology associated with deep learningCode a generative adversarial network (GAN) and a variational autoencoder (VAE) to generate images from a learned latent spaceImplement visualization techniques to compare AEs and VAEsWho this book is for This book is for aspiring data scientists and deep learning engineers who want to get started with the fundamentals of deep learning and neural networks. Although no prior knowledge of deep learning or machine learning is required, familiarity with linear algebra and Python programming is necessary to get started.



Deep Learning For Beginners


Deep Learning For Beginners
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Author : François Duval
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-12-24

Deep Learning For Beginners written by François Duval and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-24 with categories.


***** Buy now (Will soon return to $35.99)***** ***** #1 Kindle Store Bestseller in Mathematical Analysis (Throughout 2017) ***** Free Kindle eBook for customers who purchase the print book Are you thinking of learning more about Deep Learning? If you are looking for a book to help you understand how the deep learning works by using Python and Tensorflow, then this is a good book for you. Several Visual Illustrations and Examples Equations are great for really understanding every last detail of an algorithm. But to get a basic idea of how things work, this book contains several graphs which detail each neural networks/deep learning algorithms. It is contains also several graphs for the practical examples. This Is a Practical Guide Book This book will help you explore exactly what deep learning is and will also teach you about why it is so revolutionary and fascinating. The chapters will introduce the reader to the concepts, techniques, and applications of deep learning algorithms with the practical case studies and walk-through examples on which to practice. This book takes a different approach that is based on providing simple examples of how deep learning algorithms work, and building on those examples step by step to encompass the more complicated parts of the algorithms. Python and TensorFlow Codes for the Examples Shown In the Book You will build your Deep Learning Model by using Python and Tensorflow There are many ways to build a deep learning model. However, it can also be overwhelming when you start, because there are so many tools to choose. In this book, we choose only these two tools: Tensorflow and Python. Target Users The book designed for a variety of target audiences. The most suitable users would include: Newbies in computer science techniques and deep learning Professionals in data science and social sciences Professors, lecturers or tutors who are looking to find better ways to explain the content to their students in the simplest and easiest way Students and academicians, especially those focusing on neural networks and deep learning What's inside this book? Overview in Deep Learning Quick Example to start Popular Open Source Library Pre-requisite for Deep Learning Deep Learning Presentation Deep Neural Networks Applications with Tensorflow and Python Autoencoders Algorithms Deep Learning for Computer Games Anomaly Detection Glossary of Some Useful Terms in Deep Learning Useful References Frequently Asked Questions Q: Is this book for me and do I need programming experience? A: If you want to smash deep learning with Python, this book is for you. Little programming experience is required. If you already wrote a few lines of code and recognize basic programming statements, you will be OK. If not, online programming courses cover more than what it is required. You can do one in a week, for free. Q: Can I loan this book to friends? A: Yes. Under Amazon's Kindle Book Lending program, you can lend this book to friends and family for a duration of 14 days. Q: Does this book include everything I need to become a deep learning expert? A: Unfortunately, no. This book is designed for readers taking their first steps in deep learning and further learning will be required beyond this book to master all aspects of deep learning. Q: Can I have a refund if this book is not fitted for me? A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. will also be happy to help you if you send us an email at customer_service@datasciences-book.com.



Deep Learning For Beginners


Deep Learning For Beginners
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Author : Thomas Laville
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-10-30

Deep Learning For Beginners written by Thomas Laville and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-30 with categories.


Thinking of learning more in Deep Learning? Then you have landed in the right place. The overall aim of this book in Deep Learning is to explore and examine key concepts, methods and techniques used in the Deep Learning. Then you have landed in the right place. The overall aim of this book in Deep Learning is to explore and examine key concepts, methods and techniques used in the Deep Learning. This book will help you explore exactly what deep learning is and will also teach you about why it is so revolutionary and fascinating. The 11 chapters introduce the reader the concepts, techniques, application of Dep Leaning Algorithm with the practical case studies and walk-through examples to practice. By the time you are done reading this book, you will have a complete understanding as to what deep learning is and why it is such an incredible advancement in technology. Chapters in this book Introduction to Deep Learning Fundamental Concepts of Deep Learning Artificial Neural Networks Deep Neural Networks Deep Learning Applications Glossary of important terms And more Book Objectives To have an appreciation for Deep Learning and an understanding of their fundamental principles. To have an elementary adeptness in a Deep Learning Concepts and terms which includes an ability to understand the algorithms. To have an elementary understanding of (some of the) more advanced topics of Deep Learning such as Neural Networks, Deep Neural Networks. Target Users The book designed for a variety of target audiences. The most suitable users would include: 1. Newbies in Computer Science Techniques and Artificial Intelligence 2. Professionals in Data scientist and Social Sciences 3. Professors or lecturers or tutors to be in position to find better ways to explain the content to their students with simples and easiest way 4. The students and Academicians, especially those that are focusing on Deep Learning as their professionsScroll to the top and buy now to get started.



Deep Learning For Beginners


Deep Learning For Beginners
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Author : Steven Cooper
language : en
Publisher: Roland Bind
Release Date : 2018-11-06

Deep Learning For Beginners written by Steven Cooper and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-06 with Computers categories.


☆★The Best Deep Learning Book for Beginners★☆ If you are looking for a complete beginners guide to learn deep learning with examples, in just a few hours, then you need to continue reading. This book delves into the basics of deep learning for those who are enthusiasts concerning all things machine learning and artificial intelligence. For those who have seen movies which show computer systems taking over the world like, Terminator, or benevolent systems that watch over the population, i.e. Person of Interest, this should be right up your alley. This book will give you the basics of what deep learning entails. That means frameworks used by coders and significant components and tools used in deep learning, that enable facial recognition, speech recognition, and virtual assistance. Yes, deep learning provides the tools through which systems like Siri became possible. ★★ Grab your copy today and learn ★★ ♦ Deep learning utilizes frameworks which allow people to develop tools which are able to offer better abstraction, along with simplification of hard programming issues. TensorFlow is the most popular tool and is used by corporate giants such as Airbus, Twitter, and even Google. ♦ The book illustrates TensorFlow and Caffe2 as the prime frameworks that are used for development by Google and Facebook. Facebook illustrates Caffe2 as one of the lightweight and modular deep learning frameworks, though TensorFlow is the most popular one, considering it has a lot of popularity, and thus, a big forum, which allows for assistance on main problems. ♦ The book considers several components and tools of deep learning such as the neural networks; CNNs, RNNs, GANs, and auto-encoders. These algorithms create the building blocks which propel deep learning and advance it. ♦ The book also considers several applications, including chatbots and virtual assistants, which have become the main focus for deep learning into the future, as they represent the next frontier in information gathering and connectivity. The Internet of Things is also represented here, as deep learning allows for the integration of various systems via an artificial intelligence system, which is already being used for the home and car functions. ♦ And much more... The use of data science adds a lot of value to businesses, and we will continue to see the need for data scientists grow. This book is probably one of the best books for beginners. It's a step-by-step guide for any person who wants to start learning deep learning and artificial intelligence from scratch. When data science can reduce spending costs by billions of dollars in the healthcare industry, why wait to jump in? If you want to get started on deep learning and the concepts that run artificial technologies, don't wait any longer. Scroll up and click the buy now button to get this book today!



Deep Learning For Beginners


Deep Learning For Beginners
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Author : François Duval
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-01-13

Deep Learning For Beginners written by François Duval and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-13 with categories.


***** Buy now (Will soon return to $38.99 + Special Offer Below) ***** ***** #1 Kindle Store Bestseller in Computer Modelling ***** Free Kindle eBook for customers who purchase the print book from Amazon Are you thinking of learning more about Deep Learning? If you are looking for a book to help you understand concepts and algorithms of deep learning, then this is a good book for you. Several Visual Illustrations and Examples Equations are great for really understanding every last detail of an algorithm. But to get a basic idea of how things work, this book contains several graphs which detail each neural networks/deep learning algorithms. It is contains also several graphs for the practical examples. This Is a Practical Guide Book This book will help you explore exactly what deep learning is and will also teach you about why it is so revolutionary and fascinating. The chapters will introduce the reader to the concepts, techniques, and applications of deep learning algorithms with the practical case studies and walk-through examples on which to practice. This book takes a different approach that is based on providing simple examples of how deep learning algorithms work, and building on those examples step by step to encompass the more complicated parts of the algorithms. Target Users The book designed for a variety of target audiences. The most suitable users would include: Newbies in computer science techniques and deep learning Professionals in data science and social sciences Professors, lecturers or tutors who are looking to find better ways to explain the content to their students in the simplest and easiest way Students and academicians, especially those focusing on neural networks and deep learning What's inside this book? Pre-requisite for Deep Learning Introduction to Artificial Neural Networks The Basics of Artificial Neural Networks Deep Learning Evolution and Recurring Methods Relationship between machine learning and deep learning Multilayer Perceptron (MLP) Convolutional Neural Networks (CNN) Other Deep Learning Algorithms Deep Learning Applications Glossary of Some Useful Terms in Deep Learning Useful References Frequently Asked Questions Q: Is this book for me and do I need programming experience? A: If you want to learn more about deep learning, this book is for you. Little math knowledge is required. If you already have a basic notion in statistic and data science, you'll be OK. No coding experience is required. Q: Can I loan this book to friends? A: Yes. Under Amazon's Kindle Book Lending program, you can lend this book to friends and family for a duration of 14 days. Q: Does this book include everything I need to become a deep learning expert? A: Unfortunately, no. This book is designed for readers taking their first steps in deep learning and further learning will be required beyond this book to master all aspects of deep learning. Q: Can I have a refund if this book is not fitted for me? A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. will also be happy to help you if you send us an email at customer_service@datasciences-book.com.



Neural Networks For Beginners


Neural Networks For Beginners
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Author : Russel R Russo
language : en
Publisher:
Release Date : 2019-11-06

Neural Networks For Beginners written by Russel R Russo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-06 with categories.


Do you want to understand Neural Networks and learn everything about them but it looks like it is an exclusive club? Are you fascinated by Artificial Intelligence but you think that it would be too difficult for you to learn? If you think that Neural Networks and Artificial Intelligence are the present and, even more, the future of technology, and you want to be part of it... well you are in the right place, and you are looking at the right book. If you are reading these lines you have probably already noticed this: Artificial Intelligence is all around you. Your smartphone that suggests you the next word you want to type, your Netflix account that recommends you the series you may like or Spotify's personalised playlists. This is how machines are learning from you in everyday life. And these examples are only the surface of this technological revolution. Either if you want to start your own AI entreprise, to empower your business or to work in the greatest and most innovative companies, Artificial Intelligence is the future, and Neural Networks programming is the skill you want to have. The good news is that there is no exclusive club, you can easily (if you commit, of course) learn how to program and use neural networks, and to do that Neural Networks for Beginners is the perfect way. In this book you will learn: The types and components of neural networks The smartest way to approach neural network programming Why Algorithms are your friends The "three Vs" of Big Data (plus two new Vs) How machine learning will help you making predictions The three most common problems with Neural Networks and how to overcome them Even if you don't know anything about programming, Neural Networks is the perfect place to start now. Still, if you already know about programming but not about how to do it in Artificial Intelligence, neural networks are the next thing you want to learn. And Neural Networks for Beginners is the best way to do it. Download Neural Network for Beginners now to get the best start for your journey to Artificial Intelligence. Scroll to the top of the page and click the BUY NOW button.



Data Science For Beginners


Data Science For Beginners
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Author : Russel R Russo
language : en
Publisher:
Release Date : 2020-10-30

Data Science For Beginners written by Russel R Russo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-30 with categories.


Are you fascinated by Data Science but it seems too complicated? Do you want to learn everything about Artificial Intelligence but it looks like it is an exclusive club? If this is you, please keep reading: you are in the right place, looking at the right book. SInce you are reading these lines you have probably already noticed this: Artificial Intelligence is all around you. Your smartphone that suggests you the next word you want to type, your Netflix account that recommends you the series you may like or Spotify's personalised playlists. This is how machines are learning from you in everyday life. And these examples are only the surface of this technological revolution. Everyone knows (well, almost everyone) how important Data Science is for the growth and success of the biggest tech companies, and many people know about the Machine Learning impact in science, medicine and statistics. Also, it is quite commonly known that Artificial Intelligence, Machine Learning Deep Learning, and the mastering of their most important language, Python, can offer a lot of possibilities in work and business. And you yourself are probably thinking "I surely can see that opportunity, but how can I seize it?" Well, if you kept reading so far you are on the right track to answer your question. Either if you want to start your own AI entreprise, to empower your business or to work in the greatest and most innovative companies, Artificial Intelligence is the future, and Python and Neural Networks programming is The Skill you want to have. The good news is that there is no exclusive club, you can easily (if you commit, of course) learn how to find your way around Artificial Intelligence, Data Science, Deep Learning and Machine Learning, and to do that Data Science for Beginners is the best way. In Data Science for Beginners you will discover: The most effective starting points when training deep neural nets The smartest way to approach Machine Learning What libraries are and which one is the best for you Tips and tricks for a smooth and painless journey into artificial intelligence Why decision tree is the way The TensorFlow parts that are going to make your coding life easy Why python is the best language for Machine Learning How to bring your ideas into a computer How to talk with deep neural networks How to deal with variables and data The most common myths about Machine Learning debunked Even If you don't know anything about programming, understanding Data Science is the ideal place to start. Still, if you already know something about programming but not about how to apply it to Artificial Intelligence, Data Science is what you want to understand. Buy now Data Science for Beginners to start your path of Artificial Intelligence.



Machine Learning For Beginners


Machine Learning For Beginners
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Author : Samuel Hack
language : en
Publisher: Samuel Hack
Release Date : 2021-03-07

Machine Learning For Beginners written by Samuel Hack and has been published by Samuel Hack this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-07 with categories.


TODAY ONLY 55% OFF for Bookstores! Are you interested in learning about the amazing capabilities of machine learning, but you're worried it will be just too complicated? Or are you a programmer looking for a solid introduction into this field? Your customers must have this guide to understand the hidden secrets of artificial intelligence! Machine learning is an incredible technology which we're only just beginning to understand. Those who break into this industry early will reap the rewards as this field grows more and more important to businesses the world over. And the good news is, it's not too late to start! This guide breaks down the fundamentals of machine learning in a way that anyone can understand. With reference to the different kinds of machine learning models, neural networks, and the way these models learn data, you'll find everything you need to know to get started with machine learning in a concise, easy-to-understand way. Here's what you'll discover inside: What is Artificial Intelligence Really, and Why is it So Powerful? Choosing the Right Kind of Machine Learning Model for You An Introduction to Statistics Supervised and Unsupervised Learning The Power of Neural Networks Reinforcement Learning and Ensemble Modeling "Random Forests" and Decision Trees Must-Have Programming Tools And Much More! Whether you're already a programmer or if you're a complete beginner, now you can break into machine learning in no time! Covering all the basics from simple decision trees to the complex decision-making processes which mirror our own brains, Machine Learning for Beginners is your comprehensive introduction to this amazing field! Buy it NOW and let your customers become to addicted to this incredible book!



Python Machine Learning For Beginners


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!



Deep Learning For Coders With Fastai And Pytorch


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