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Machine Learning for Healthcare Analytics Projects
Machine Learning for Healthcare Analytics Projects

Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics. This book will teach you how to implement key machine learning algorithms and walk you through their use cases by employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors ( ...
Impractical Python Projects
Impractical Python Projects

Impractical Python Projects picks up where the complete beginner books leave off, expanding on existing concepts and introducing new tools that you'll use every day. And to keep things interesting, each project includes a zany twist featuring historical incidents, pop culture references, and literary allusions. You'll flex your problem-solving skills and employ Python's many useful libraries to do things like: Help James Bond crack a high-tech safe with a hill-climbing algorithm; Write haiku poems using Markov Chain Analysis; Use genetic algorithms to breed a race of gigantic rats; Crack the world's most successful military cipher using cryptanalysis; Foil corporate security with invisible electronic ink; Derive the anagram, "I am Lord Voldemort" using linguistical sieves; Plan your parents secure retirement with Monte Carlo simulation; Save the sorceress Zatanna from a stabby death using palingrams; Model the Milky Way and calculate our odds of detecting alien civilizations; Help t ...
Mission Python
Mission Python

Launch into coding with Mission Python, a space-themed guide to building a complete computer game in Python. You'll learn programming fundamentals like loops, strings, and lists as you build Escape!, an exciting game with a map to explore, items to collect, and tricky logic puzzles to solve. As you work through the book, you'll build exercises and mini-projects, like making a spacewalk simulator and creating an astronaut's safety checklist that will put your new Python skills to the test. You'll learn how to use Pygame Zero, a free resource that lets you add graphics and sound effects to your creations, and you'll get useful game-making tips, such as how to design fun puzzles and intriguing maps. Before you know it, you'll have a working, awesome game to stump your friends with (and some nifty coding skills, too!). You can follow this book using a Raspberry Pi or a Microsoft Windows PC, and the 3D graphics and sound effects you need are provided as a download. ...
Collect, Combine, and Transform Data Using Power Query in Excel and Power BI
Collect, Combine, and Transform Data Using Power Query in Excel and Power BI

Using Power Query, you can import, reshape, and cleanse any data from a simple interface, so you can mine that data for all of its hidden insights. Power Query is embedded in Excel, Power BI, and other Microsoft products, and leading Power Query expert Gil Raviv will help you make the most of it. Discover how to eliminate time-consuming manual data preparation, solve common problems, avoid pitfalls, and more. Then, walk through several complete analytics challenges, and integrate all your skills in a realistic chapter-length final project. By the time you're finished, you'll be ready to wrangle any data - and transform it into actionable knowledge. Prepare and analyze your data the easy way, with Power Query; Quickly prepare data for analysis with Power Query in Excel (also known as Get & Transform) and in Power BI; Solve common data preparation problems with a few mouse clicks and simple formula edits; Combine data from multiple sources, multiple queries, and mismatched tables; Mas ...
R Graphics Cookbook, 2nd Edition
R Graphics Cookbook, 2nd Edition

R Graphics Cookbook provides more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly - without having to comb through all the details of R's graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project and includes a discussion of how and why the recipe works. Most of the recipes in this second edition use the updated version of the ggplot2 package, a powerful and flexible way to make graphs in R. You'll also find expanded content about the visual design of graphics. If you have at least a basic understanding of the R language, you're ready to get started with this easy-to-use reference. Use R's default graphics for quick exploration of data; Create a variety of bar graphs, line graphs, and scatter plots; Summarize data distributions with histograms, density curves, box plots, and more; Provide annotations to help viewers interpret data; Control the overall appearance of ...
Django 2 Web Development Cookbook, 3rd Edition
Django 2 Web Development Cookbook, 3rd Edition

Django is a framework designed to balance rapid web development with high performance. It handles high levels of user traffic and interaction, integrates with a variety of databases, and collects and processes data in real time. This book follows a task-based approach to guide you through developing with the Django 2.1 framework, starting with setting up and configuring Docker containers and a virtual environment for your project. You'll learn how to write reusable pieces of code for your models and manage database changes. You'll work with forms and views to enter and list data, applying practical examples using templates and JavaScript together for the optimum user experience. This cookbook helps you to adjust the built-in Django administration to fit your needs and sharpen security and performance to make your web applications as robust, scalable, and dependable as possible. You'll also explore integration with Django CMS, the popular content management suite. In the final cha ...
Mastering Flask Web Development, 2nd Edition
Mastering Flask Web Development, 2nd Edition

Flask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web Development will take you on a complete tour of the Flask environment and teach you how to build a production-ready application. You'll begin by learning about the installation of Flask and basic concepts such as MVC and accessing a database using an ORM. You will learn how to structure your application so that it can scale to any size with the help of Flask Blueprints. You'll then learn how to use Jinja2 templates with a high level of expertise. You will also learn how to develop with SQL or NoSQL databases, and how to develop REST APIs and JWT authentication. Next, you'll move on to build role-based access security and authentication using LDAP, OAuth, OpenID, and database. Also learn how to create asynchronous tasks that can scale to any load using Celery and RabbitMQ or Redis. You will also be introduced to a wide range of Flask extensions to leverage technologies such as cache, ...
R Web Scraping Quick Start Guide
R Web Scraping Quick Start Guide

Web scraping is a technique to extract data from websites. It simulates the behavior of a website user to turn the website itself into a web service to retrieve or introduce new data. This book gives you all you need to get started with scraping web pages using R programming. You will learn about the rules of RegEx and Xpath, key components for scraping website data. We will show you web scraping techniques, methodologies, and frameworks. With this book's guidance, you will become comfortable with the tools to write and test RegEx and XPath rules. We will focus on examples of dynamic websites for scraping data and how to implement the techniques learned. You will learn how to collect URLs and then create XPath rules for your first web scraping script using rvest library. From the data you collect, you will be able to calculate the statistics and create R plots to visualize them. Finally, you will discover how to use Selenium drivers with R for more sophisticated scraping. You ...
Apache Hadoop 3 Quick Start Guide
Apache Hadoop 3 Quick Start Guide

Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS. The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems. The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, ...
Python Deep Learning Projects
Python Deep Learning Projects

Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system. Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects. By the end of ...
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