Neural Networks For Beginners
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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.
Neural Networks
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Author : Herbert Jones
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-08-09
Neural Networks written by Herbert Jones 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 2018-08-09 with categories.
If you want to learn about Neural Networks then keep reading... Aladdin from "The Arabian Nights" had a magic lamp that fulfilled his every wish when rubbed. Today we have a smartphone that serves as a window to a whole universe of knowledge, entertainment and even wise personal assistants, such as Siri - all we have to do is rub the screen. Aladdin's lamp was powered by a genie, but what powers Siri? Neural networks. It's an astounding concept that tries to mimic the way living brains work by amalgamating human and machine ways of thinking. The goal of this book is to present the reader with a digestible, readable explanation of neural networks while keeping the underlying concepts intact. The reader will acquire fundamental knowledge of neural networks through loosely related chapters that nonetheless reference terms and ideas mentioned throughout the book. The book itself isn't meant to be strictly academic, but a blend of colloquial and technical that brings this exciting, yet eerie, topic to the widest swath of the general public. There is a lot of coding and math behind neural networks, but the reader is presumed to have no prior knowledge or interest in either, so the concepts are broken down and elaborated on as such. Each chapter is made as standalone as possible to allow the reader to skip back and forth without getting lost, with the glossary at the very end serving as a handy summary. Where possible, references have been included to support the presented conclusions and encourage the reader to scrutinize the traditional media in search of clues. Neural Networks: An Essential Beginners Guide to Artificial Neural Networks and their Role in Machine Learning and Artificial Intelligence cover topics such as: Programming a smart(er) computer Composition Giving neural networks legs to stand on The magnificent wetware Personal assistants Tracking users in the real world Self-driving neural networks Taking everyone's job Quantum leap in computing Attacks on neural networks Neural network war Ghost in the machine No backlash And Much, Much More So if you want to learn about Neural Networks without having to go through heavy textbooks, click "add to cart"!
Neural Networks For Beginners
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Author : daniel Huston
language : en
Publisher: Lulu.com
Release Date : 2023-05-01
Neural Networks For Beginners written by daniel Huston and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-01 with Computers categories.
"Neural Networks for Beginners" is a beginner-friendly guide to understanding the basics of neural networks, machine learning, and deep learning. Written in simple language, this book provides a comprehensive introduction to the key concepts and techniques used in neural networks. Starting with an overview of the history and importance of neural networks, the book covers the basics of machine learning and deep learning, including their differences and applications. It then delves into the different types of neural networks, their architectures, and how they are trained and optimized. The book also provides real-world examples of successful neural network applications in various fields, such as healthcare, finance, and technology. It explains how neural networks are used in practical applications, such as image recognition, speech recognition, and natural language processing. "Neural Networks for Beginners" is perfect for anyone with no prior knowledge of neural networks who wants to learn about this exciting field. Whether you are a student, researcher, or professional, this book will provide you with the knowledge and skills needed to get started with neural networks. With this book, you'll gain a solid understanding of the basics of neural networks and be prepared to explore and leverage their power. I. Introduction Explanation of neural networks and their applications Neural networks are a type of machine learning algorithm that is modeled after the structure and function of the human brain. They are designed to identify patterns in data and learn from them in order to make predictions or classifications. One of the key applications of neural networks is in image and speech recognition, where the network is trained on large datasets of images or audio files, and can then accurately identify and classify new images or audio recordings. Neural networks can also be used for natural language processing, where they can be trained to understand and respond to written or spoken language. Neural networks are also used in finance for fraud detection and risk assessment, in healthcare for disease diagnosis and treatment planning, in transportation for autonomous vehicles, and in many other fields. One of the main advantages of neural networks is their ability to learn and improve over time, as more data is fed into the network. This makes them ideal for applications where accuracy is critical and where the underlying patterns may be complex
Neural Networks For Beginners
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Author : Bob Story
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-07-15
Neural Networks For Beginners written by Bob Story 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 2017-07-15 with categories.
Discover How to Build Your Own Neural Network From Scratch...Even if You've Got Zero Math or Coding Skills! What seemed like a lame and unbelievable sci-fi movie a few decades ago is now a reality. Machines can finally think. Maybe not quite as complex as the human brain, but more than enough to make everyone's life a lot easier. Artificial neural networks, based on the neurons found in the human brain give machines a 'brain'. Patterned just like biological neurons, these software or hardware are a variety of the deep learning technology. With their help you can make your computer learn by feeding it data, which will then be generated as the output you desire. It is they to thank for the nanoseconds in which computers operate. It may be science, but it is not actually rocket science. Everyone can learn how to take advantage of the progressed technology of today, get inside the 'brain' of the computers, and train them to perform the desired operations. They have been used in many different industries, and you can rest assured that you will find the perfect purpose for your own neural network. The best part about this book is that it doesn't require a college degree. Your high school math skills are quite enough for you to get a good grasp of the basics and learn how to build an artificial neural network. From non-mathematical explanations to teaching you the basic math behind the ANNs and training you how to actually program one, this book is the most helpful guide you will ever find. Carefully designed for you, the beginner, this guide will help you become a proud owner of a neural network in no time. Here's a Sneak Peak to What You'll Discover Inside this Book: The 6 unique benefits of neural networks The difference between biological and artificial neural networks And inside look into ANN (Artificial Neural Networks) The industries ANN is used in How to teach neural networks to perform specific commands The different types of learning modalities (e.g. Hebbian Learning, unsupervised learning, supervised learning etc.) The architecture of ANN Basic math behind artificial neurons Simple networks for pattern classification The Hebb Rule How to build a simple neural network code The backpropogation algorithm and how to program it And much, much more! There's a lot more inside this book we'll cover, so be prepared. I've made to lucidly explain everything I cover so that there's zero confusion! Download this book today and discover all the intricate details of building your very own Neural Network
Convolutional Neural Networks In Python
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Author : Frank Millstein
language : en
Publisher: Frank Millstein
Release Date : 2020-07-06
Convolutional Neural Networks In Python written by Frank Millstein and has been published by Frank Millstein this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-06 with Computers categories.
Convolutional Neural Networks in Python This book covers the basics behind Convolutional Neural Networks by introducing you to this complex world of deep learning and artificial neural networks in a simple and easy to understand way. It is perfect for any beginner out there looking forward to learning more about this machine learning field. This book is all about how to use convolutional neural networks for various image, object and other common classification problems in Python. Here, we also take a deeper look into various Keras layer used for building CNNs we take a look at different activation functions and much more, which will eventually lead you to creating highly accurate models able of performing great task results on various image classification, object classification and other problems. Therefore, at the end of the book, you will have a better insight into this world, thus you will be more than prepared to deal with more complex and challenging tasks on your own. Here Is a Preview of What You’ll Learn In This Book… Convolutional neural networks structure How convolutional neural networks actually work Convolutional neural networks applications The importance of convolution operator Different convolutional neural networks layers and their importance Arrangement of spatial parameters How and when to use stride and zero-padding Method of parameter sharing Matrix multiplication and its importance Pooling and dense layers Introducing non-linearity relu activation function How to train your convolutional neural network models using backpropagation How and why to apply dropout CNN model training process How to build a convolutional neural network Generating predictions and calculating loss functions How to train and evaluate your MNIST classifier How to build a simple image classification CNN And much, much more! Get this book NOW and learn more about Convolutional Neural Networks in Python!
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 And Artificial Intelligence
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Author : John Slavio
language : en
Publisher:
Release Date : 2019-07-24
Deep Learning And Artificial Intelligence written by John Slavio and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-24 with Computers categories.
Welcome to this book on Deep Learning and Neural Networks. We're going to be diving into what neural networks are, what the current neural networks out there do, with an API. Once we go over how everything works and how each of these new technologies work, we will go over the many different applications in general life and business. There have been a lot of news stories about how there are going to be self-driving cars, machines that make their own products, and many other different applications of neural networks that make it sound like a vastly complicated machine. However, the tool of the neural network is a very simple tool. When you hear about the applications that are being created that utilize neural networks, you are actually hearing about the amount of work that went behind making a neural network do something that's complicated but not a complicated neural network. Neural networks are extremely easy to understand as you will find throughout this book but the problem is that people have made them look complicated. Therefore, let's go ahead and demystify this subject so that you can get into the field of neural networks yourself and have some fun. Here's What's Included In This Book: What are Neural Networks? Biological Neural Networks Artificial Neural Networks Keras Model and Layers Different Deep Learning Algorithms Benefits of Neural Networks Business Applications of Neural Networks
Artificial Neural Networks For Beginners
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Author : Lalm Philip
language : en
Publisher: Independently Published
Release Date : 2025-12-10
Artificial Neural Networks For Beginners written by Lalm Philip and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-10 with Computers categories.
Artificial Neural Networks for Beginners Essential Concepts, Tools, and Techniques to Build Your First AI Models By Lalm Philip Are you curious about Artificial Intelligence but don't know where to start? Do neural networks sound complicated, confusing, or overwhelmingly technical? This book was written to change that. Artificial Neural Networks for Beginners is a clear, practical, and friendly introduction to one of the most powerful technologies in the modern world. Whether you're a student, an aspiring programmer, or simply someone fascinated by how machines learn, this book will guide you step-by-step from the basics to building your very first AI models. Inside, you'll discover: ✔ Simple Explanations of Core Concepts Learn what neurons, weights, biases, activation functions, and layers really are - explained in plain language with zero assumptions. ✔ How Neural Networks Actually Learn Understand forward propagation, loss functions, and backpropagation using intuitive examples designed for absolute beginners. ✔ The Most Important Activation Functions See how Sigmoid, ReLU, and Tanh influence learning - and when to use each one. ✔ The Main Types of Neural Networks Get a beginner-friendly look at Feedforward, Convolutional, and Recurrent Neural Networks, plus when each is most useful. ✔ Build Your First Neural Network Follow a gentle, structured path to setting up and training your own simple model. ✔ Solve Common Beginner Challenges Overfitting, underfitting, noisy data, choosing model size - explained with practical tips you can use immediately. ✔ Real-World Applications Explore how neural networks power image recognition, language processing, predictive analytics, and more, with relatable examples. ✔ Beginner-Friendly Advanced Topics Dive into deep learning basics, transfer learning, hyperparameter tuning, and optimization - without being overwhelmed. ✔ Your Roadmap for Continued Growth Discover the best resources, communities, and project ideas to continue your AI journey with confidence.
Data Science For Beginners
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Author : Russel R Russo
language : en
Publisher:
Release Date : 2020-12-17
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 2020-12-17 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.
Artificial Neural Networks
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Author : Kevin L. Priddy
language : en
Publisher: SPIE Press
Release Date : 2005
Artificial Neural Networks written by Kevin L. Priddy and has been published by SPIE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
This tutorial text provides the reader with an understanding of artificial neural networks (ANNs), and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed, and the data collection processes, to the many ways ANNs are being used today. The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach the engineer the guiding principles necessary to use and apply artificial neural networks.