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Hands-On Machine Learning with C++
Hands-On Machine Learning with C++

C++ can make your machine learning models run faster and more efficiently. This handy guide will help you learn the fundamentals of machine learning (ML), showing you how to use C++ libraries to get the most out of your data. This book makes machine learning with C++ for beginners easy with its example-based approach, demonstrating how to implement supervised and unsupervised ML algorithms through real-world examples. This book will get you hands-on with tuning and optimizing a model for different use cases, assisting you with model selection and the measurement of performance. You'll cover techniques such as product recommendations, ensemble learning, and anomaly detection using modern C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib. Next, you'll explore neural networks and deep learning using examples such as image classification and sentiment analysis, which will help you solve various problems. Later, you'll learn how to handle production and de ...
TypeScript Quickly
TypeScript Quickly

TypeScript is JavaScript with an important upgrade! By adding a strong type system to JavaScript, TypeScript can help you eliminate entire categories of runtime errors. In TypeScript Quickly, you'll learn to build rock-solid apps through practical examples and hands-on projects under the expert instruction of experienced web developers Yakov Fain and Anton Moiseev. Strong typing can eliminate nearly all errors caused by unanticipated data values. With TypeScript, an enhanced version of JavaScript, you can specify types and type annotations so your code is easier to read and far less likely to fail at runtime. And because the core of TypeScript is standard JavaScript, it runs on all major browsers and can be used with frameworks like Angular, Vue, and React. TypeScript Quickly teaches you to exploit the benefits of types in browser-based and standalone applications. In this practical guide, you'll build a fascinating blockchain service app that takes you through a range of type-se ...
Succeeding with AI
Succeeding with AI

Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Succeeding with AI sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It's filled with practical techniques for running data science programs that ensure they're cost effective and focused on the right business goals. Succeeding with AI requires talent, tools, and money. So why do many well-funded, state-of-the-art projects fail to deliver meaningful business value? Because talent, tools, and money aren't enough: You also need to know how to ask the right questions. In this unique book, AI consultant Veljko Krunic reveals a tested process to start AI projects right, so you'll get the results you want. Succeeding with AI sets out a framework for pl ...
Mastering Large Datasets with Python
Mastering Large Datasets with Python

Modern data science solutions need to be clean, easy to read, and scalable. In Mastering Large Datasets with Python, author J.T. Wolohan teaches you how to take a small project and scale it up using a functionally influenced approach to Python coding. You'll explore methods and built-in Python tools that lend themselves to clarity and scalability, like the high-performing parallelism method, as well as distributed technologies that allow for high data throughput. The abundant hands-on exercises in this practical tutorial will lock in these essential skills for any large-scale data science project. Programming techniques that work well on laptop-sized data can slow to a crawl - or fail altogether - when applied to massive files or distributed datasets. By mastering the powerful map and reduce paradigm, along with the Python-based tools that support it, you can write data-centric applications that scale efficiently without requiring codebase rewrites as your requirements change. Ma ...
Machine Learning with R, the tidyverse, and mlr
Machine Learning with R, the tidyverse, and mlr

Machine learning (ML) is a collection of programming techniques for discovering relationships in data. With ML algorithms, you can cluster and classify data for tasks like making recommendations or fraud detection and make predictions for sales trends, risk analysis, and other forecasts. Once the domain of academic data scientists, machine learning has become a mainstream business process, and tools like the easy-to-learn R programming language put high-quality data analysis in the hands of any programmer. Machine Learning with R, the tidyverse, and mlr teaches you widely used ML techniques and how to apply them to your own datasets using the R programming language and its powerful ecosystem of tools. This book will get you started! Machine Learning with R, the tidyverse, and mlr gets you started in machine learning using R Studio and the awesome mlr machine learning package. This practical guide simplifies theory and avoids needlessly complicated statistics or math. All core ML tec ...
Elm in Action
Elm in Action

Elm is more than just a cutting-edge programming language, it's a chance to upgrade the way you think about building web applications. Once you get comfortable with Elm's refreshingly different approach to application development, you'll be working with a clean syntax, dependable libraries, and a delightful compiler that essentially eliminates runtime exceptions. Elm compiles to JavaScript, so your code runs in any browser, and Elm's best-in-class rendering speed will knock your socks off. Let's get started! Simply put, the Elm programming language transforms the way you think about frontend web development. Elm's legendary compiler is an incredible assistant, giving you the precise and user-friendly support you need to work efficiently. Elm applications have small bundle sizes that run faster than JavaScript frameworks and are famously easy to maintain as they grow. The catch? Elm isn't JavaScript, so you'll have some new skills to learn. Elm in Action teaches you the Elm lan ...
Spark in Action, 2nd Edition
Spark in Action, 2nd Edition

The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, 2nd Edition, you'll learn to take advantage of Spark's core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning. Spark skills are a hot commodity in enterprises worldwide, and with Spark's powerful and flexible Java APIs, you can reap all the benefits without first learning Scala or Hadoop. Analyzing enterprise data starts by reading, filtering, and merging files and streams from many sources. The Spark data processing engine handles this varied volume like a champ, delivering speeds 100 times faster than Hadoop systems. Thanks to SQL support, an intuitive interface, and a straightforward multilanguage API, you can use Spark without learning a complex new ecosystem. Spark in Action, 2nd Edition, teaches you to create end-to-end analytics ...
Hacking Secret Ciphers with Python
Hacking Secret Ciphers with Python

There are many books that teach beginners how to write secret messages using ciphers. There are a couple books that teach beginners how to hack ciphers. As far as I can tell, there are no books to teach beginners how to write programs to hack ciphers. This book fills that gap. This book is for complete beginners who do not know anything about encryption, hacking, or cryptography. The ciphers in this book (except for the RSA cipher in the last chapter) are all centuries old, and modern computers now have the computational power to hack their encrypted messages. No modern organization or individuals use these ciphers anymore. As such, there's no reasonable context in which you could get into legal trouble for the information in this book. ...
The SQL Server DBA's Guide to Docker Containers
The SQL Server DBA's Guide to Docker Containers

Get introduced to the world of Docker containers from a SQL Server DBA's perspective. This book explains container technology and how it can improve the deployment of your SQL Server databases without infrastructure lock-in. You will be equipped with the right technical skills to guide stakeholders in your business as they adopt and adapt to new technologies to improve time-to-market and competitiveness. You will learn how to build a lab environment at home on which to build skills that transfer directly into your day job. This book teaches you how to install and configure Docker on both Windows Server and Linux operating systems. You will learn the most common Docker commands that you need to know as a DBA to deploy and manage SQL Server on containers. Support for SQL Server on Linux is new, and this book has your back with guidance on creating Docker images specifically for deployment to a Linux platform. Included is coverage of key Linux commands needed to manage SQL Server on th ...
Understanding System.IO for .NET Core 3
Understanding System.IO for .NET Core 3

Take full advantage of the .NET APIs in System.IO to achieve fundamental I/O operations and produce better quality software. You'll start with the basics of creating a .NET Core custom library for System.IO. You will learn the purpose and benefits of a custom cross-platform .NET Core library along with the implementation architecture of the custom library components. Moving forward, you will learn how to use the .NET APIs of System.IO for getting information about resources. Here, you will go through drives, directories, files, and much more in the .NET API. You'll discuss manipulation of resources and the environment, where you will learn how to build custom IO actions for resource manipulation followed by its properties and security. Next, you will learn special .NET API operations with System.IO with demonstrations on working with collection of resources, directories, files, and system information. Finally, you will go through the managed and unmanaged streams in the .NET API ...
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