Machine Learning For Beginners: An Introduction for Beginners, Why Machine Learning Matters Today and How Machine Learning Networks, Algorithms, Conce, Cooper Steven
If you're looking to become familiar with the basics of a neural network, then you have found a resource to help you accomplish that goal. If you require an approach that is mostly non-mathematical, then read on.
Did you see how I've introduced filtering parameters to achieve the best match from this book to its suitable reader? You've just observed the technical way a neural network performs
I will "train" your neural network and reduce your "cost score." Don't worry, that sentence will make perfect sense to you soon...
In other words, this book will teach you in an effort to minimize any gaps or errors in your understanding.
Within the book "Neural Networks", you ll discover:
What a neural network is
How deep learning works
The technical components that give rise to machine intelligence
Terms, jargon, and the mathematical elements of a neural network
The different types of neural networks
The ability to explain a neural network to others, while simultaneously being able to build on this knowledge without being COMPLETELY LOST
How to hack a neural network
How to build your own neural network
This, along with a bit of history, practical implications, and much, much more
You'll be an Einstein in no time And even if you are already up to speed on the topic, this book has the power to illustrate what a neural network is in a way that is capable of inspiring new approaches and technical improvements. The world can't wait to see what you can do
If you easily sort out information that is presented in a practical and relatable form, then the real-world examples and narratives contained in this book will optimize your understanding.
If you're looking for a way to become an expert in machine learning, then keep reading...
Machine learning is an incredibly dense topic. It's hard to imagine condensing it into an easily readable and digestible format. However, this book aims to do exactly that.
Throughout the course of this book, we're going to be covering numerous different aspects of machine learning, such as:
The different types of learning algorithm that you can expect to encounter
The numerous applications of machine learning
The future of machine learning
What neural networks and deep learning are
The best practices for picking up machine learning
What languages and libraries to work with
The different types of machine learning and how they differ
The various problems that you can solve with machine learning algorithms
And much more...
Starting from nothing, we slowly work our way through all the concepts that are central to machine learning. By the end of this book, you're going to feel as though you have an extremely firm understanding of what machine learning is, how it can be used, and most importantly, how it can change the world. You're also going to have an understanding of the logic behind the algorithms and what they aim to accomplish.
Don't waste your time working with a book that's only going to make an already complicated topic even more complicated. Pick up this book and learn everything you need to know in no time
Описание: These books provide proven concepts and strategies for people who want to know more about deep learning and how to work with data. After reading this bundle you`ll be able to choose the right kind of architecture, how to build a system that can learn, how to train it, and then how to use it to accomplish your goals.
2 books in 1 This is the bundle of two successful books in the market
Book 1: In "Deep Learning for Beginners: A comprehensive introduction of deep learning fundamentals for beginners to understanding frameworks, neural networks, large datasets, and creative applications with ease" you will 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...
Book 2: In "Data Science from Scratch: The #1 Data Science Guide for Everything A Data Scientist Needs to Know: Python, Linear Algebra, Statistics, Coding, Applications, Neural Networks, and Decision Trees" you will learn:
In-depth information about what data science is and why it is important.
The prerequisites you will need to get started in data science.
What it means to be a data scientist.
The roles that hacking and coding play in data science.
The different coding languages that can be used in data science.
Why python is so important.
How to use linear algebra and statistics.
The different applications for data science.
How to work with the data through munging and cleaning.
And much more...
These books provide proven concepts and strategies for people who want to know more about deep learning and how to work with data. After reading this bundle you'll be able to choose the right kind of architecture, how to build a system that can learn, how to train it, and then how to use it to accomplish your goals.
Get your copy of these fantastic guides to master state-of-the-art, deep learning algorithms and their implementation
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 that 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 that allow people to develop tools that 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 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 our economy, why wait to jump in?
If you're looking to become familiar with the basics of a neural network, then you have found a resource to help you accomplish that goal. If you require an approach that is mostly non-mathematical, then read on.
Did you see how I've introduced filtering parameters to achieve the best match from this book to its suitable reader? You've just observed the technical way a neural network performs
I will "train" your neural network and reduce your "cost score." Don't worry, that sentence will make perfect sense to you soon...
In other words, this book will teach you in an effort to minimize any gaps or errors in your understanding.
Within the book "Neural Networks", you ll discover:
What a neural network is
How deep learning works
The technical components that give rise to machine intelligence
Terms, jargon, and the mathematical elements of a neural network
The different types of neural networks
The ability to explain a neural network to others, while simultaneously being able to build on this knowledge without being COMPLETELY LOST
How to hack a neural network
How to build your own neural network
This, along with a bit of history, practical implications, and much, much more
You'll be an Einstein in no time And even if you are already up to speed on the topic, this book has the power to illustrate what a neural network is in a way that is capable of inspiring new approaches and technical improvements. The world can't wait to see what you can do
If you easily sort out information that is presented in a practical and relatable form, then the real-world examples and narratives contained in this book will optimize your understanding.
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 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 our economy, why wait to jump in?
Автор: Parsons Steven T., Cooper Callum E. Название: Paracoustics: Sound & the Paranormal ISBN: 1910121320 ISBN-13(EAN): 9781910121320 Издательство: Неизвестно Цена: 3102.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This unique book examines that fascination and presents a selection of the leading research in paranormal acoustics together with an in-depth review of the equipment and techniques that are used by researchers and investigators.
