Building Machine Learning Systems with Python, 3rd Edition
Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Lea ...
Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Lea ...
ASP.NET Core 2 and Vue.js
This book will walk you through the process of developing an e-commerce application from start to finish, utilizing an ASP.NET Core web API and Vue.js Single-Page Application (SPA) frontend. We will build the application using a feature slice approach, whereby in each chapter we will add the required frontend and backend changes to complete an entire feature. In the early chapters, we'll keep things fairly simple to get you started, but by the end of the book, you'll be utilizing some advanced concepts, such as server-side rendering and continuous integration and deployment. You will learn how to set up and configure a modern development environment for building ASP.NET Core web APIs and Vue.js SPA frontends. You will also learn about how ASP.NET Core differs from its predecessors, and how we can utilize those changes to our benefit. Finally, you will learn the fundamentals of building modern frontend applications using Vue.js, as well as some of the more advanced concepts, which ...
This book will walk you through the process of developing an e-commerce application from start to finish, utilizing an ASP.NET Core web API and Vue.js Single-Page Application (SPA) frontend. We will build the application using a feature slice approach, whereby in each chapter we will add the required frontend and backend changes to complete an entire feature. In the early chapters, we'll keep things fairly simple to get you started, but by the end of the book, you'll be utilizing some advanced concepts, such as server-side rendering and continuous integration and deployment. You will learn how to set up and configure a modern development environment for building ASP.NET Core web APIs and Vue.js SPA frontends. You will also learn about how ASP.NET Core differs from its predecessors, and how we can utilize those changes to our benefit. Finally, you will learn the fundamentals of building modern frontend applications using Vue.js, as well as some of the more advanced concepts, which ...
R Deep Learning Essentials, 2nd Edition
Deep learning is a powerful subset of machine learning that is very successful in domains such as computer vision and natural language processing (NLP). This second edition of R Deep Learning Essentials will open the gates for you to enter the world of neural networks by building powerful deep learning models using the R ecosystem. This book will introduce you to the basic principles of deep learning and teach you to build a neural network model from scratch. As you make your way through the book, you will explore deep learning libraries, such as Keras, MXNet, and TensorFlow, and create interesting deep learning models for a variety of tasks and problems, including structured data, computer vision, text data, anomaly detection, and recommendation systems. You'll cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud. In the concluding chapters, you will learn about the theoretical concepts of deep learning ...
Deep learning is a powerful subset of machine learning that is very successful in domains such as computer vision and natural language processing (NLP). This second edition of R Deep Learning Essentials will open the gates for you to enter the world of neural networks by building powerful deep learning models using the R ecosystem. This book will introduce you to the basic principles of deep learning and teach you to build a neural network model from scratch. As you make your way through the book, you will explore deep learning libraries, such as Keras, MXNet, and TensorFlow, and create interesting deep learning models for a variety of tasks and problems, including structured data, computer vision, text data, anomaly detection, and recommendation systems. You'll cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud. In the concluding chapters, you will learn about the theoretical concepts of deep learning ...
Applied Deep Learning with Python
Taking an approach that uses the latest developments in the Python ecosystem, you'll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. We'll explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. It's okay if these terms seem overwhelming; we'll show you how to put them to work. We'll build upon our classification coverage by taking a quick look at ethical web scraping and interactive visualizations to help you professionally gather and present your analysis. It's after this that we start building out our keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data. By guiding you through a trained neural network, we'll explore common deep learning network architec ...
Taking an approach that uses the latest developments in the Python ecosystem, you'll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. We'll explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. It's okay if these terms seem overwhelming; we'll show you how to put them to work. We'll build upon our classification coverage by taking a quick look at ethical web scraping and interactive visualizations to help you professionally gather and present your analysis. It's after this that we start building out our keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data. By guiding you through a trained neural network, we'll explore common deep learning network architec ...
Learning Bootstrap 4 by Building Projects
Bootstrap, the world's most popular frontend framework, is an open source toolkit for building web applications with HTML, CSS, and JavaScript. Learning Bootstrap 4 by Building Projects covers the essentials of Bootstrap 4 along with best practices. The book begins by introducing you to the latest features of Bootstrap 4. You will learn different elements and components of Bootstrap, such as the strict grid system, Sass, which replaced Less, flexbox, Font Awesome, and cards. As you make your way through the chapters, you will use a template that will help you to build different kinds of real-world websites, such as a social media website, a company landing page, a media hosting website, and a profile page, with ease. By the end of this book, you will have built websites that are visually appealing, responsive, and robust. ...
Bootstrap, the world's most popular frontend framework, is an open source toolkit for building web applications with HTML, CSS, and JavaScript. Learning Bootstrap 4 by Building Projects covers the essentials of Bootstrap 4 along with best practices. The book begins by introducing you to the latest features of Bootstrap 4. You will learn different elements and components of Bootstrap, such as the strict grid system, Sass, which replaced Less, flexbox, Font Awesome, and cards. As you make your way through the chapters, you will use a template that will help you to build different kinds of real-world websites, such as a social media website, a company landing page, a media hosting website, and a profile page, with ease. By the end of this book, you will have built websites that are visually appealing, responsive, and robust. ...
Getting to Know Vue.js
Learn how to render lists of items without repeating your code structure and how to work with conditional rendering items and event handling. Containing all you need to know to get started with Vue.js, this book will take you through using build tools (transpile to ES5), creating custom components, state management, and routers. With Getting to Know Vue.js, you'll see how to combine reusable code with custom components, allowing you to create snippets of reusable code to suit your specific business needs. You'll also explore how to use Single File Components and the Vue.js Command Line Interface (CLI) to build components in a single file and add in build tools as you see fit. Getting started with a new Single Page Application (SPA) JavaScript framework can be an overwhelming task, but Vue.js makes this daunting task simple and easy to learn, allowing you to start implementing business needs with just a script reference to the library and the custom JavaScript required for your u ...
Learn how to render lists of items without repeating your code structure and how to work with conditional rendering items and event handling. Containing all you need to know to get started with Vue.js, this book will take you through using build tools (transpile to ES5), creating custom components, state management, and routers. With Getting to Know Vue.js, you'll see how to combine reusable code with custom components, allowing you to create snippets of reusable code to suit your specific business needs. You'll also explore how to use Single File Components and the Vue.js Command Line Interface (CLI) to build components in a single file and add in build tools as you see fit. Getting started with a new Single Page Application (SPA) JavaScript framework can be an overwhelming task, but Vue.js makes this daunting task simple and easy to learn, allowing you to start implementing business needs with just a script reference to the library and the custom JavaScript required for your u ...
Keras Reinforcement Learning Projects
Reinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks. Keras Reinforcement Learning Projects installs human-level performance into your applications using algorithms and techniques of reinforcement learning, coupled with Keras, a faster experimental library. The book begins with getting you up and running with the concepts of reinforcement learning using Keras. You'll learn how to simulate a random walk using Markov chains and select the best portfolio using dynamic programming (DP) and Python. You'll also explore projects such as forecasting stock prices using Monte Carlo methods, delivering vehicle routing application using Temporal Distance (TD) learning algorithms, and balancing a Rotating Mechanical System using Markov decision processes. Once you've understood the basics, you'll move on to Modeling of a Segway, running a robot control system using deep reinforcement learning ...
Reinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks. Keras Reinforcement Learning Projects installs human-level performance into your applications using algorithms and techniques of reinforcement learning, coupled with Keras, a faster experimental library. The book begins with getting you up and running with the concepts of reinforcement learning using Keras. You'll learn how to simulate a random walk using Markov chains and select the best portfolio using dynamic programming (DP) and Python. You'll also explore projects such as forecasting stock prices using Monte Carlo methods, delivering vehicle routing application using Temporal Distance (TD) learning algorithms, and balancing a Rotating Mechanical System using Markov decision processes. Once you've understood the basics, you'll move on to Modeling of a Segway, running a robot control system using deep reinforcement learning ...
Python Reinforcement Learning Projects
Reinforcement learning is one of the most exciting and rapidly growing fields in machine learning. This is due to the many novel algorithms developed and incredible results published in recent years. In this book, you will learn about the core concepts of RL including Q-learning, policy gradients, Monte Carlo processes, and several deep reinforcement learning algorithms. As you make your way through the book, you'll work on projects with datasets of various modalities including image, text, and video. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore technologies such as TensorFlow and OpenAI Gym to implement deep learning reinforcement learning algorithms that also predict stock prices, generate natural language, and even build other neural networks. By the end of this book, you will have hands-on experience with eight reinforcement learning projects, each addressing different topics and/or algorithms. We ho ...
Reinforcement learning is one of the most exciting and rapidly growing fields in machine learning. This is due to the many novel algorithms developed and incredible results published in recent years. In this book, you will learn about the core concepts of RL including Q-learning, policy gradients, Monte Carlo processes, and several deep reinforcement learning algorithms. As you make your way through the book, you'll work on projects with datasets of various modalities including image, text, and video. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore technologies such as TensorFlow and OpenAI Gym to implement deep learning reinforcement learning algorithms that also predict stock prices, generate natural language, and even build other neural networks. By the end of this book, you will have hands-on experience with eight reinforcement learning projects, each addressing different topics and/or algorithms. We ho ...
Deep Learning By Example
Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid unders ...
Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid unders ...
TensorFlow Machine Learning Cookbook, 2nd Edition
TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of ...
TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of ...