Author: Hadelin de Ponteves
Publisher: Packt Publishing Ltd
ISBN: 1838645551
Category : Computers
Languages : en
Pages : 361
Book Description
Unlock the power of artificial intelligence with top Udemy AI instructor Hadelin de Ponteves. Key FeaturesLearn from friendly, plain English explanations and practical activitiesPut ideas into action with 5 hands-on projects that show step-by-step how to build intelligent softwareUse AI to win classic video games and construct a virtual self-driving carBook Description Welcome to the Robot World ... and start building intelligent software now! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. What you will learnMaster the basics of AI without any previous experienceBuild fun projects, including a virtual-self-driving car and a robot warehouse workerUse AI to solve real-world business problemsLearn how to code in PythonDiscover the 5 principles of reinforcement learningCreate your own AI toolkitWho this book is for If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).
AI Crash Course
Author: Hadelin de Ponteves
Publisher: Packt Publishing Ltd
ISBN: 1838645551
Category : Computers
Languages : en
Pages : 361
Book Description
Unlock the power of artificial intelligence with top Udemy AI instructor Hadelin de Ponteves. Key FeaturesLearn from friendly, plain English explanations and practical activitiesPut ideas into action with 5 hands-on projects that show step-by-step how to build intelligent softwareUse AI to win classic video games and construct a virtual self-driving carBook Description Welcome to the Robot World ... and start building intelligent software now! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. What you will learnMaster the basics of AI without any previous experienceBuild fun projects, including a virtual-self-driving car and a robot warehouse workerUse AI to solve real-world business problemsLearn how to code in PythonDiscover the 5 principles of reinforcement learningCreate your own AI toolkitWho this book is for If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).
Publisher: Packt Publishing Ltd
ISBN: 1838645551
Category : Computers
Languages : en
Pages : 361
Book Description
Unlock the power of artificial intelligence with top Udemy AI instructor Hadelin de Ponteves. Key FeaturesLearn from friendly, plain English explanations and practical activitiesPut ideas into action with 5 hands-on projects that show step-by-step how to build intelligent softwareUse AI to win classic video games and construct a virtual self-driving carBook Description Welcome to the Robot World ... and start building intelligent software now! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. What you will learnMaster the basics of AI without any previous experienceBuild fun projects, including a virtual-self-driving car and a robot warehouse workerUse AI to solve real-world business problemsLearn how to code in PythonDiscover the 5 principles of reinforcement learningCreate your own AI toolkitWho this book is for If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).
AI Crash Course
Author: Hadelin de Ponteves
Publisher:
ISBN: 9781838645359
Category : Computers
Languages : en
Pages : 360
Book Description
This friendly and accessible guide to AI theory and programming in Python requires no maths or data science background. Key Features Roll up your sleeves and start programming AI models No math, data science, or machine learning background required Packed with hands-on examples, illustrations, and clear step-by-step instructions 5 hands-on working projects put ideas into action and show step-by-step how to build intelligent software Book Description AI is changing the world - and with this book, anyone can start building intelligent software! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Taking a graduated approach that starts with the basics before easing readers into more complicated formulas and notation, Hadelin helps you understand what you really need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming: Google Colab Python TensorFlow Keras PyTorch AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. What you will learn Master the key skills of deep learning, reinforcement learning, and deep reinforcement learning Understand Q-learning and deep Q-learning Learn from friendly, plain English explanations and practical activities Build fun projects, including a virtual-self-driving car Use AI to solve real-world business problems and win classic video games Build an intelligent, virtual robot warehouse worker Who this book is for If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).
Publisher:
ISBN: 9781838645359
Category : Computers
Languages : en
Pages : 360
Book Description
This friendly and accessible guide to AI theory and programming in Python requires no maths or data science background. Key Features Roll up your sleeves and start programming AI models No math, data science, or machine learning background required Packed with hands-on examples, illustrations, and clear step-by-step instructions 5 hands-on working projects put ideas into action and show step-by-step how to build intelligent software Book Description AI is changing the world - and with this book, anyone can start building intelligent software! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Taking a graduated approach that starts with the basics before easing readers into more complicated formulas and notation, Hadelin helps you understand what you really need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming: Google Colab Python TensorFlow Keras PyTorch AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. What you will learn Master the key skills of deep learning, reinforcement learning, and deep reinforcement learning Understand Q-learning and deep Q-learning Learn from friendly, plain English explanations and practical activities Build fun projects, including a virtual-self-driving car Use AI to solve real-world business problems and win classic video games Build an intelligent, virtual robot warehouse worker Who this book is for If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).
Crash Course in Digital Technology
Author: Louis E. Frenzel
Publisher: Newnes
ISBN: 9780750697095
Category : Technology & Engineering
Languages : en
Pages : 214
Book Description
Crash Course in Digital Technology teaches the basics of digital electronics theory and circuits in an easy-to-understand format. Each chapter includes learning objectives, clear explanations and examples, and an end-of-chapter self-quiz. The drill-and-review software included with the book allows learners to test themselves on the contents of each chapter, providing a second reinforcement of the material. A final chapter teaches the basics of troubleshooting digital circuits. With the two other Crash Course books, Electronics Technology and Microprocessor Technology, this book forms a complete course in electronics and microcomputer technology appropriate for technical schools, industrial training, and hobbyists. Louis Frenzel is an experienced electronics engineer and educator, as well as the author of many magazine articles and texts. He is currently an instructor at Austin Community College in Austin, Texas. Drill-and-review software included Clear, easy format Self-paced introduction to digital electronics
Publisher: Newnes
ISBN: 9780750697095
Category : Technology & Engineering
Languages : en
Pages : 214
Book Description
Crash Course in Digital Technology teaches the basics of digital electronics theory and circuits in an easy-to-understand format. Each chapter includes learning objectives, clear explanations and examples, and an end-of-chapter self-quiz. The drill-and-review software included with the book allows learners to test themselves on the contents of each chapter, providing a second reinforcement of the material. A final chapter teaches the basics of troubleshooting digital circuits. With the two other Crash Course books, Electronics Technology and Microprocessor Technology, this book forms a complete course in electronics and microcomputer technology appropriate for technical schools, industrial training, and hobbyists. Louis Frenzel is an experienced electronics engineer and educator, as well as the author of many magazine articles and texts. He is currently an instructor at Austin Community College in Austin, Texas. Drill-and-review software included Clear, easy format Self-paced introduction to digital electronics
Deep Learning for Coders with fastai and PyTorch
Author: Jeremy Howard
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624
Book Description
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
Publisher: O'Reilly Media
ISBN: 1492045497
Category : Computers
Languages : en
Pages : 624
Book Description
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
Python Crash Course
Author: Eric Matthes
Publisher: No Starch Press
ISBN: 1593277393
Category : Computers
Languages : en
Pages : 564
Book Description
Python Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time. In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s super-handy libraries, and a simple web app you can deploy online. As you work through Python Crash Course you’ll learn how to: –Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal –Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses –Work with data to generate interactive visualizations –Create and customize Web apps and deploy them safely online –Deal with mistakes and errors so you can solve your own programming problems If you’ve been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code! Uses Python 2 and 3
Publisher: No Starch Press
ISBN: 1593277393
Category : Computers
Languages : en
Pages : 564
Book Description
Python Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time. In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s super-handy libraries, and a simple web app you can deploy online. As you work through Python Crash Course you’ll learn how to: –Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal –Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses –Work with data to generate interactive visualizations –Create and customize Web apps and deploy them safely online –Deal with mistakes and errors so you can solve your own programming problems If you’ve been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code! Uses Python 2 and 3
Statistics Crash Course for Beginners
Author: Ai Publishing
Publisher:
ISBN: 9781734790160
Category :
Languages : en
Pages : 330
Book Description
Frequentist and Bayesian Statistics Crash Course for Beginners Data and statistics are the core subjects of Machine Learning (ML). The reality is the average programmer may be tempted to view statistics with disinterest. But if you want to exploit the incredible power of Machine Learning, you need a thorough understanding of statistics. The reason is a Machine Learning professional develops intelligent and fast algorithms that learn from data. Frequentist and Bayesian Statistics Crash Course for Beginners presents you with an easy way of learning statistics fast. Contrary to popular belief, statistics is no longer the exclusive domain of math Ph.D.s. It's true that statistics deals with numbers and percentages. Hence, the subject can be very dry and boring. This book, however, transforms statistics into a fun subject. Frequentist and Bayesian statistics are two statistical techniques that interpret the concept of probability in different ways. Bayesian statistics was first introduced by Thomas Bayes in the 1770s. Bayesian statistics has been instrumental in the design of high-end algorithms that make accurate predictions. So even after 250 years, the interest in Bayesian statistics has not faded. In fact, it has accelerated tremendously. Frequentist Statistics is just as important as Bayesian Statistics. In the statistical universe, Frequentist Statistics is the most popular inferential technique. In fact, it's the first school of thought you come across when you enter the statistics world. How Is This Book Different? AI Publishing is completely sold on the learning by doing methodology. We have gone to great lengths to ensure you find learning statistics easy. The result: you will not get stuck along your learning journey. This is not a book full of complex mathematical concepts and difficult equations. You will find that the coverage of the theoretical aspects of statistics is proportionate to the practical aspects of the subject. The book makes the reading process easier by presenting you with three types of box-tags in different colors. They are: Requirements, Further Readings, and Hands-on Time. The final chapter presents two mini-projects to give you a better understanding of the concepts you studied in the previous eight chapters. The main feature is you get instant access to a treasure trove of all the related learning material when you buy this book. They include PDFs, Python codes, exercises, and references--on the publisher's website. You get access to all this learning material at no extra cost. You can also download the Machine Learning datasets used in this book at runtime. Alternatively, you can access them through the Resources/Datasets folder. The quick course on Python programming in the first chapter will be immensely helpful, especially if you are new to Python. Since you can access all the Python codes and datasets, a computer with the internet is sufficient to get started. The topics covered include: A Quick Introduction to Python for Statistics Starting with Probability Random Variables and Probability Distributions Descriptive Statistics: Measure of Central Tendency and Spread Exploratory Analysis: Data Visualization Statistical Inference Frequentist Inference Bayesian Inference Hands-on Projects Click the BUY NOW button and start your Statistics Learning journey.
Publisher:
ISBN: 9781734790160
Category :
Languages : en
Pages : 330
Book Description
Frequentist and Bayesian Statistics Crash Course for Beginners Data and statistics are the core subjects of Machine Learning (ML). The reality is the average programmer may be tempted to view statistics with disinterest. But if you want to exploit the incredible power of Machine Learning, you need a thorough understanding of statistics. The reason is a Machine Learning professional develops intelligent and fast algorithms that learn from data. Frequentist and Bayesian Statistics Crash Course for Beginners presents you with an easy way of learning statistics fast. Contrary to popular belief, statistics is no longer the exclusive domain of math Ph.D.s. It's true that statistics deals with numbers and percentages. Hence, the subject can be very dry and boring. This book, however, transforms statistics into a fun subject. Frequentist and Bayesian statistics are two statistical techniques that interpret the concept of probability in different ways. Bayesian statistics was first introduced by Thomas Bayes in the 1770s. Bayesian statistics has been instrumental in the design of high-end algorithms that make accurate predictions. So even after 250 years, the interest in Bayesian statistics has not faded. In fact, it has accelerated tremendously. Frequentist Statistics is just as important as Bayesian Statistics. In the statistical universe, Frequentist Statistics is the most popular inferential technique. In fact, it's the first school of thought you come across when you enter the statistics world. How Is This Book Different? AI Publishing is completely sold on the learning by doing methodology. We have gone to great lengths to ensure you find learning statistics easy. The result: you will not get stuck along your learning journey. This is not a book full of complex mathematical concepts and difficult equations. You will find that the coverage of the theoretical aspects of statistics is proportionate to the practical aspects of the subject. The book makes the reading process easier by presenting you with three types of box-tags in different colors. They are: Requirements, Further Readings, and Hands-on Time. The final chapter presents two mini-projects to give you a better understanding of the concepts you studied in the previous eight chapters. The main feature is you get instant access to a treasure trove of all the related learning material when you buy this book. They include PDFs, Python codes, exercises, and references--on the publisher's website. You get access to all this learning material at no extra cost. You can also download the Machine Learning datasets used in this book at runtime. Alternatively, you can access them through the Resources/Datasets folder. The quick course on Python programming in the first chapter will be immensely helpful, especially if you are new to Python. Since you can access all the Python codes and datasets, a computer with the internet is sufficient to get started. The topics covered include: A Quick Introduction to Python for Statistics Starting with Probability Random Variables and Probability Distributions Descriptive Statistics: Measure of Central Tendency and Spread Exploratory Analysis: Data Visualization Statistical Inference Frequentist Inference Bayesian Inference Hands-on Projects Click the BUY NOW button and start your Statistics Learning journey.
The Crash Course
Author: Chris Martenson
Publisher: John Wiley & Sons
ISBN: 1118013123
Category : Business & Economics
Languages : en
Pages : 336
Book Description
The next twenty years will be completely unlike the last twenty years. The world is in economic crisis, and there are no easy fixes to our predicament. Unsustainable trends in the economy, energy, and the environment have finally caught up with us and are converging on a very narrow window of time—the "Twenty-Teens." The Crash Course presents our predicament and illuminates the path ahead, so you can face the coming disruptions and thrive--without fearing the future or retreating into denial. In this book you will find solid facts and grounded reasoning presented in a calm, positive, non-partisan manner. Our money system places impossible demands upon a finite world. Exponentially rising levels of debt, based on assumptions of future economic growth to fund repayment, will shudder to a halt and then reverse. Unfortunately, our financial system does not operate in reverse. The consequences of massive deleveraging will be severe. Oil is essential for economic growth. The reality of dwindling oil supplies is now internationally recognized, yet virtually no developed nations have a Plan B. The economic risks to individuals, companies, and countries are varied and enormous. Best-case, living standards will drop steadily worldwide. Worst-case, systemic financial crises will toss the world into jarring chaos. This book is written for those who are motivated to learn about the root causes of our predicaments, protect themselves and their families, mitigate risks as much as possible, and control what effects they can. With challenge comes opportunity, and The Crash Course offers a positive vision for how to reshape our lives to be more balanced, resilient, and sustainable.
Publisher: John Wiley & Sons
ISBN: 1118013123
Category : Business & Economics
Languages : en
Pages : 336
Book Description
The next twenty years will be completely unlike the last twenty years. The world is in economic crisis, and there are no easy fixes to our predicament. Unsustainable trends in the economy, energy, and the environment have finally caught up with us and are converging on a very narrow window of time—the "Twenty-Teens." The Crash Course presents our predicament and illuminates the path ahead, so you can face the coming disruptions and thrive--without fearing the future or retreating into denial. In this book you will find solid facts and grounded reasoning presented in a calm, positive, non-partisan manner. Our money system places impossible demands upon a finite world. Exponentially rising levels of debt, based on assumptions of future economic growth to fund repayment, will shudder to a halt and then reverse. Unfortunately, our financial system does not operate in reverse. The consequences of massive deleveraging will be severe. Oil is essential for economic growth. The reality of dwindling oil supplies is now internationally recognized, yet virtually no developed nations have a Plan B. The economic risks to individuals, companies, and countries are varied and enormous. Best-case, living standards will drop steadily worldwide. Worst-case, systemic financial crises will toss the world into jarring chaos. This book is written for those who are motivated to learn about the root causes of our predicaments, protect themselves and their families, mitigate risks as much as possible, and control what effects they can. With challenge comes opportunity, and The Crash Course offers a positive vision for how to reshape our lives to be more balanced, resilient, and sustainable.
AP Environmental Science Crash Course
Author: Gayle Evans
Publisher: Research & Education Assoc.
ISBN: 0738609315
Category : Study Aids
Languages : en
Pages : 290
Book Description
REA's AP Environmental Science Crash Course is the first book of its kind for the last-minute studier or any AP student who wants a quick refresher on the course. /Written by an AP Environmental Science teacher, the targeted review chapters prepare students for the test by only focusing on the important topics tested on the AP Environmental Science exam. /The easy-to-read review chapters in outline format cover everything AP students need to know for the exam: human population dynamics, managing public lands, energy conservation, changes in Earth's climate, species extinction, loss of biodiversity, and more. The author also includes must-know key terms all AP students should know before test day. /With our Crash Course, students can study the subject faster, learn the crucial material, and boost their AP score all in less time. The author provides key strategies for answering the multiple-choice questions, so students can build their point scores and get a 5!
Publisher: Research & Education Assoc.
ISBN: 0738609315
Category : Study Aids
Languages : en
Pages : 290
Book Description
REA's AP Environmental Science Crash Course is the first book of its kind for the last-minute studier or any AP student who wants a quick refresher on the course. /Written by an AP Environmental Science teacher, the targeted review chapters prepare students for the test by only focusing on the important topics tested on the AP Environmental Science exam. /The easy-to-read review chapters in outline format cover everything AP students need to know for the exam: human population dynamics, managing public lands, energy conservation, changes in Earth's climate, species extinction, loss of biodiversity, and more. The author also includes must-know key terms all AP students should know before test day. /With our Crash Course, students can study the subject faster, learn the crucial material, and boost their AP score all in less time. The author provides key strategies for answering the multiple-choice questions, so students can build their point scores and get a 5!
Mathematics for Machine Learning
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
Book Description
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
Book Description
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Natural Language Processing Crash Course for Beginners
Author: Ai Publishing
Publisher:
ISBN: 9781734790139
Category :
Languages : en
Pages : 342
Book Description
Natural Language Processing Crash Course for Beginners Artificial Intelligence (AI) isn't the latest fad! The reason is AI has been around since 1956, and its relevance is evident in every field today. Artificial Intelligence incorporates human intelligence into machines. Machine Learning (ML), a branch of AI, enables machines to learn by themselves. Deep Learning (DL), a subfield of Machine Learning, uses algorithms that are inspired by the functioning of the human brain. Natural Language Processing (NLP) combines computational linguistics and Artificial Intelligence, enabling computers and humans to communicate seamlessly. And NLP is immensely powerful and impactful as every business is looking to integrate it into their day to day dealings. How Is This Book Different? This book by AI Publishing is carefully crafted, giving equal importance to the theoretical concepts as well as the practical aspects of natural language processing. In each chapter of the second half of the book, the theoretical concepts of different types of deep learning and NLP techniques have been covered in-depth, followed by practical examples. You will learn how to apply different NLP techniques using the TensorFlow and Keras libraries for Python. Each chapter contains exercises that are designed to evaluate your understanding of the concepts covered in that chapter. Also, in the Resources section of each chapter, you can access the Python notebook. The author has also compiled a list of hands-on NLP projects and competitions that you can try on your own. The main benefit of purchasing this book is you get immediate access to all the extra learning material presented with this book--Python codes, exercises, PDFs, and references--on the publisher's website without having to spend an extra cent. You can download the datasets used in this book at runtime, or you can access them in the Resources/Datasets folder. The author holds your hand through everything. He provides you a step by step explanation of the installation of the software needed to implement the various NLP techniques in this book. You can start experimenting with the practical aspects of NLP right from the beginning. Even if you are new to Python, you'll find the ultra-short course on Python programming language in the second chapter immensely helpful. You get all the codes and datasets with this book. So, if you have access to a computer with the internet, you can get started. The topics covered include: What is Natural Language Processing? Environment Setup and Python Crash Course Introduction to Deep Learning Text Cleaning and Manipulation Common NLP Tasks Importing Text Data from Various Sources Word Embeddings: Converting Words to Numbers IMDB Movies Sentimental Analysis Ham and Spam Message Classification Text Summarization and Topic Modeling Text Classification with Deep Learning Text Translation Using Seq2Seq Model State of the Art NLP with BERT Transformers Hands-on NLP Projects/Articles for Practice Exercise Solutions Click the BUY button and download the book now to start your Natural Language Processing journey.
Publisher:
ISBN: 9781734790139
Category :
Languages : en
Pages : 342
Book Description
Natural Language Processing Crash Course for Beginners Artificial Intelligence (AI) isn't the latest fad! The reason is AI has been around since 1956, and its relevance is evident in every field today. Artificial Intelligence incorporates human intelligence into machines. Machine Learning (ML), a branch of AI, enables machines to learn by themselves. Deep Learning (DL), a subfield of Machine Learning, uses algorithms that are inspired by the functioning of the human brain. Natural Language Processing (NLP) combines computational linguistics and Artificial Intelligence, enabling computers and humans to communicate seamlessly. And NLP is immensely powerful and impactful as every business is looking to integrate it into their day to day dealings. How Is This Book Different? This book by AI Publishing is carefully crafted, giving equal importance to the theoretical concepts as well as the practical aspects of natural language processing. In each chapter of the second half of the book, the theoretical concepts of different types of deep learning and NLP techniques have been covered in-depth, followed by practical examples. You will learn how to apply different NLP techniques using the TensorFlow and Keras libraries for Python. Each chapter contains exercises that are designed to evaluate your understanding of the concepts covered in that chapter. Also, in the Resources section of each chapter, you can access the Python notebook. The author has also compiled a list of hands-on NLP projects and competitions that you can try on your own. The main benefit of purchasing this book is you get immediate access to all the extra learning material presented with this book--Python codes, exercises, PDFs, and references--on the publisher's website without having to spend an extra cent. You can download the datasets used in this book at runtime, or you can access them in the Resources/Datasets folder. The author holds your hand through everything. He provides you a step by step explanation of the installation of the software needed to implement the various NLP techniques in this book. You can start experimenting with the practical aspects of NLP right from the beginning. Even if you are new to Python, you'll find the ultra-short course on Python programming language in the second chapter immensely helpful. You get all the codes and datasets with this book. So, if you have access to a computer with the internet, you can get started. The topics covered include: What is Natural Language Processing? Environment Setup and Python Crash Course Introduction to Deep Learning Text Cleaning and Manipulation Common NLP Tasks Importing Text Data from Various Sources Word Embeddings: Converting Words to Numbers IMDB Movies Sentimental Analysis Ham and Spam Message Classification Text Summarization and Topic Modeling Text Classification with Deep Learning Text Translation Using Seq2Seq Model State of the Art NLP with BERT Transformers Hands-on NLP Projects/Articles for Practice Exercise Solutions Click the BUY button and download the book now to start your Natural Language Processing journey.