Distributed Machine Learning with Python
Reducing time cost in machine learning leads to a shorter waiting time for model training and a faster model updating cycle. Distributed machine learning enables machine learning practitioners to shorten model training and inference time by orders of magnitude. With the help of this practical guide, you'll be able to put your Python development knowledge to work to get up and running with the implementation of distributed machine learning, including multi-node machine learning systems, in no time. You'll begin by exploring how distributed systems work in the machine learning area and how distributed machine learning is applied to state-of-the-art deep learning models. As you advance, you'll see how to use distributed systems to enhance machine learning model training and serving speed. You'll also get to grips with applying data parallel and model parallel approaches before optimizing the in-parallel model training and serving pipeline in local clusters or cloud environments. By the en ...
Reducing time cost in machine learning leads to a shorter waiting time for model training and a faster model updating cycle. Distributed machine learning enables machine learning practitioners to shorten model training and inference time by orders of magnitude. With the help of this practical guide, you'll be able to put your Python development knowledge to work to get up and running with the implementation of distributed machine learning, including multi-node machine learning systems, in no time. You'll begin by exploring how distributed systems work in the machine learning area and how distributed machine learning is applied to state-of-the-art deep learning models. As you advance, you'll see how to use distributed systems to enhance machine learning model training and serving speed. You'll also get to grips with applying data parallel and model parallel approaches before optimizing the in-parallel model training and serving pipeline in local clusters or cloud environments. By the en ...
Natural Language Processing with Flair
Flair is an easy-to-understand natural language processing (NLP) framework designed to facilitate training and distribution of state-of-the-art NLP models for named entity recognition, part-of-speech tagging, and text classification. Flair is also a text embedding library for combining different types of embeddings, such as document embeddings, Transformer embeddings, and the proposed Flair embeddings. Natural Language Processing with Flair takes a hands-on approach to explaining and solving real-world NLP problems. You'll begin by installing Flair and learning about the basic NLP concepts and terminology. You will explore Flair's extensive features, such as sequence tagging, text classification, and word embeddings, through practical exercises. As you advance, you will train your own sequence labeling and text classification models and learn how to use hyperparameter tuning in order to choose the right training parameters. You will learn about the idea behind one-shot and few-shot ...
Flair is an easy-to-understand natural language processing (NLP) framework designed to facilitate training and distribution of state-of-the-art NLP models for named entity recognition, part-of-speech tagging, and text classification. Flair is also a text embedding library for combining different types of embeddings, such as document embeddings, Transformer embeddings, and the proposed Flair embeddings. Natural Language Processing with Flair takes a hands-on approach to explaining and solving real-world NLP problems. You'll begin by installing Flair and learning about the basic NLP concepts and terminology. You will explore Flair's extensive features, such as sequence tagging, text classification, and word embeddings, through practical exercises. As you advance, you will train your own sequence labeling and text classification models and learn how to use hyperparameter tuning in order to choose the right training parameters. You will learn about the idea behind one-shot and few-shot ...
Beginning MicroPython with the Raspberry Pi Pico
Program the Raspberry Pi Pico, the latest microcontroller board from raspberrypi.org, with MicroPython. This book will take you on a tour of the Raspberry Pi Pico, including how to get started using the microcontroller, seeing which alternative microcontrollers are available, and how to connect and run simple code examples. You'll program example projects in MicroPython using Python on your PC as a learning platform. Then build your hardware skillset working with electronics and breadboard circuits. You'll implement example projects with all steps explained, including hardware connections and executing the project. Then apply them to real-world, approachable projects using the accessible Raspberry Pi Pico! The book shows how the cloud is used for IoT data and find out what popular cloud systems currently exist for IoT. Finally, you'll use ThingSpeak for hosting IoT data including connecting your Pico to the Internet. Beginning MicroPython with the Raspberry Pi Pico allows y ...
Program the Raspberry Pi Pico, the latest microcontroller board from raspberrypi.org, with MicroPython. This book will take you on a tour of the Raspberry Pi Pico, including how to get started using the microcontroller, seeing which alternative microcontrollers are available, and how to connect and run simple code examples. You'll program example projects in MicroPython using Python on your PC as a learning platform. Then build your hardware skillset working with electronics and breadboard circuits. You'll implement example projects with all steps explained, including hardware connections and executing the project. Then apply them to real-world, approachable projects using the accessible Raspberry Pi Pico! The book shows how the cloud is used for IoT data and find out what popular cloud systems currently exist for IoT. Finally, you'll use ThingSpeak for hosting IoT data including connecting your Pico to the Internet. Beginning MicroPython with the Raspberry Pi Pico allows y ...
Building Python Web APIs with FastAPI
RESTful web services are commonly used to create APIs for web-based applications owing to their light weight and high scalability. This book will show you how FastAPI, a high-performance web framework for building RESTful APIs in Python, allows you to build robust web APIs that are simple and intuitive and makes it easy to build quickly with very little boilerplate code. This book will help you set up a FastAPI application in no time and show you how to use FastAPI to build a REST API that receives and responds to user requests. You'll go on to learn how to handle routing and authentication while working with databases in a FastAPI application. The book walks you through the four key areas: building and using routes for create, read, update, and delete (CRUD) operations; connecting the application to SQL and NoSQL databases; securing the application built; and deploying your application locally or to a cloud environment. By the end of this book, you'll have developed a solid unde ...
RESTful web services are commonly used to create APIs for web-based applications owing to their light weight and high scalability. This book will show you how FastAPI, a high-performance web framework for building RESTful APIs in Python, allows you to build robust web APIs that are simple and intuitive and makes it easy to build quickly with very little boilerplate code. This book will help you set up a FastAPI application in no time and show you how to use FastAPI to build a REST API that receives and responds to user requests. You'll go on to learn how to handle routing and authentication while working with databases in a FastAPI application. The book walks you through the four key areas: building and using routes for create, read, update, and delete (CRUD) operations; connecting the application to SQL and NoSQL databases; securing the application built; and deploying your application locally or to a cloud environment. By the end of this book, you'll have developed a solid unde ...
Exploring Graphs with Elixir
Data is everywhere - it's just not very well connected, which makes it super hard to relate dataset to dataset. Using graphs as the underlying glue, you can readily join data together and create navigation paths across diverse sets of data. Add Elixir, with its awesome power of concurrency, and you'll soon be mastering data networks. Learn how different graph models can be accessed and used from within Elixir and how you can build a robust semantics overlay on top of graph data structures. We'll start from the basics and examine the main graph paradigms. Get ready to embrace the world of connected data! Graphs provide an intuitive and highly flexible means for organizing and querying huge amounts of loosely coupled data items. These data networks, or graphs in math speak, are typically stored and queried using graph databases. Elixir, with its noted support for fault tolerance and concurrency, stands out as a language eminently suited to processing sparsely connected and distribute ...
Data is everywhere - it's just not very well connected, which makes it super hard to relate dataset to dataset. Using graphs as the underlying glue, you can readily join data together and create navigation paths across diverse sets of data. Add Elixir, with its awesome power of concurrency, and you'll soon be mastering data networks. Learn how different graph models can be accessed and used from within Elixir and how you can build a robust semantics overlay on top of graph data structures. We'll start from the basics and examine the main graph paradigms. Get ready to embrace the world of connected data! Graphs provide an intuitive and highly flexible means for organizing and querying huge amounts of loosely coupled data items. These data networks, or graphs in math speak, are typically stored and queried using graph databases. Elixir, with its noted support for fault tolerance and concurrency, stands out as a language eminently suited to processing sparsely connected and distribute ...
.NET Performance Testing and Optimization
As we develop the applications to meet current and future needs, it is only natural to use current best practices and techniques for our designs and implementations. In the quest to improve how we develop, we can access a true wealth of information which is available on design patterns, object-oriented analysis, low-level code techniques and language features. The technology community is full of articles, blog posts, books, and videos describing things such as generics, how to implement the observer pattern, LINQ to SQL techniques, CSS tricks, and a host of other topics. These points are often easily described in a single post or article, wherein a thorough dissemination of the technique can be presented, and readers and viewers can quickly gain a much better understanding of the technique or point in question. Indeed, when broken down into individual and easily digestible components, almost anything complex becomes much easier to grasp. From the point of view of sophisticated de ...
As we develop the applications to meet current and future needs, it is only natural to use current best practices and techniques for our designs and implementations. In the quest to improve how we develop, we can access a true wealth of information which is available on design patterns, object-oriented analysis, low-level code techniques and language features. The technology community is full of articles, blog posts, books, and videos describing things such as generics, how to implement the observer pattern, LINQ to SQL techniques, CSS tricks, and a host of other topics. These points are often easily described in a single post or article, wherein a thorough dissemination of the technique can be presented, and readers and viewers can quickly gain a much better understanding of the technique or point in question. Indeed, when broken down into individual and easily digestible components, almost anything complex becomes much easier to grasp. From the point of view of sophisticated de ...
3D Deep Learning with Python
With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time. Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library. By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. ...
With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time. Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library. By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. ...
Supercharging Node.js Applications with Sequelize
Continuous changes in business requirements can make it difficult for programmers to organize business logic into database models, which turns out to be an expensive operation as changes to the database may result in errors and incongruity within applications. Supercharging Node.js Applications with Sequelize helps you get to grips with Sequelize, a reliable ORM that enables you to alleviate these issues in your database and applications. With Sequelize, you'll no longer need to store information in flat files or memory. This book takes a hands-on approach to implementation and associated methodologies for your database that will have you up and running in no time. You'll learn how to configure Sequelize for your Node.js application properly, develop a better sense of understanding of how this ORM works, and find out how to manage your database from Node.js using Sequelize. Finally, you'll be able to use Sequelize as the database driver for building your application from scratch. ...
Continuous changes in business requirements can make it difficult for programmers to organize business logic into database models, which turns out to be an expensive operation as changes to the database may result in errors and incongruity within applications. Supercharging Node.js Applications with Sequelize helps you get to grips with Sequelize, a reliable ORM that enables you to alleviate these issues in your database and applications. With Sequelize, you'll no longer need to store information in flat files or memory. This book takes a hands-on approach to implementation and associated methodologies for your database that will have you up and running in no time. You'll learn how to configure Sequelize for your Node.js application properly, develop a better sense of understanding of how this ORM works, and find out how to manage your database from Node.js using Sequelize. Finally, you'll be able to use Sequelize as the database driver for building your application from scratch. ...
Deep Learning with TensorFlow and Keras, 3rd Edition
Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natura ...
Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natura ...
Django 4 By Example, 4th Edition
Django 4 By Example is the 4th edition of the best-selling franchise that helps you build web apps. This book will walk you through the creation of real-world applications, solving common problems, and implementing best practices using a step-by-step approach. You'll cover a wide range of web app development topics as you build four different apps: A blog application: Create data models, views, and URLs and implement an admin site for your blog. Create sitemaps and RSS feeds and implement a full-text search engine with PostgreSQL. A social website: Implement authentication with Facebook, Twitter, and Google. Create user profiles, image thumbnails, a bookmarklet, and an activity stream. Implement a user follower system and add infinite scroll pagination to your website. An e-commerce application: Build a product catalog, a shopping cart, and asynchronous tasks with Celery and RabbitMQ. Process payments with Stripe and manage payment notifications via webhooks. Build a produc ...
Django 4 By Example is the 4th edition of the best-selling franchise that helps you build web apps. This book will walk you through the creation of real-world applications, solving common problems, and implementing best practices using a step-by-step approach. You'll cover a wide range of web app development topics as you build four different apps: A blog application: Create data models, views, and URLs and implement an admin site for your blog. Create sitemaps and RSS feeds and implement a full-text search engine with PostgreSQL. A social website: Implement authentication with Facebook, Twitter, and Google. Create user profiles, image thumbnails, a bookmarklet, and an activity stream. Implement a user follower system and add infinite scroll pagination to your website. An e-commerce application: Build a product catalog, a shopping cart, and asynchronous tasks with Celery and RabbitMQ. Process payments with Stripe and manage payment notifications via webhooks. Build a produc ...