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Podcasts
NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a work?ow for building NLP applications.We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn.We conclude by deploying these models as REST APIs with Flask.By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges.
Windows Presentation Foundation is rich in possibilities when it comes to delivering an excellent user experience. This book will show you how to build professional-grade applications that look great and work smoothly.We start by providing you with a foundation of knowledge to improve your workflow – this includes teaching you how to build the base layer of the application, which will support all that comes after it. We’ll also cover the useful details of data binding. Next, we cover the user interface and show you how to get the most out of the built-in and custom WPF controls. The final section of the book demonstrates ways to polish your applications, from adding practical animations and data validation to improving application performance. The book ends with a tutorial on how to deploy your applications and outlines potential ways to apply your new-found knowledge so you can put it to use right away.
Phoenix is a modern web development framework that is used to build API’s and web applications. It is built on Elixir and runs on Erlang VM which makes it much faster than other options. With Elixir and Phoenix, you build your application the right way, ready to scale and ready for the increasing demands of real-time web applications.This book covers the basics of the Phoenix web framework, showing you how to build a community voting application, and is divided into three parts. In the first part, you will be introduced to Phoenix and Elixir and understand the core terminologies that are used to describe them. You will also learn to build controller pages, store and retrieve data, add users to your app pages and protect your database. In the second section you will be able to reinforce your knowledge of architecting real time applications in phoenix and not only debug these applications but also diagnose issues in them. In the third and final section you will have the complete understanding of deploying and running the phoenix application and should be comfortable to make your first application releaseBy the end of this book, you'll have a strong grasp of all of the core fundamentals of the Phoenix framework, and will have built a full production-ready web application from scratch.
C++ is one of the most widely used programming languages. Fast, efficient, and flexible, it is used to solve many problems. The latest versions of C++ have seen programmers change the way they code, giving up on the old-fashioned C-style programming and adopting modern C++ instead.Beginning with the modern language features, each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. You will learn major concepts about the core programming language as well as common tasks faced while building a wide variety of software. You will learn about concepts such as concurrency, performance, meta-programming, lambda expressions, regular expressions, testing, and many more in the form of recipes. These recipes will ensure you can make your applications robust and fast.By the end of the book, you will understand the newer aspects of C++11/14/17 and will be able to overcome tasks that are time-consuming or would break your stride while developing.
React Cookbook. Create dynamic web apps with React using Redux, Webpack, Node.js, and GraphQL
React.js is Facebook's dynamic frontend web development framework. It helps you build efficient, high-performing web applications with an intuitive user interface.With more than 66 practical and self-contained tutorials, this book examines common pain points and best practices for building web applications with React. Each recipe addresses a specific problem and offers a proven solution with insights into how it works, so that you can modify the code and configuration files to suit your requirements.The React Cookbook starts with recipes for installing and setting up the React.js environment with the Create React Apps tool. You’ll understand how to build web components, forms, animations, and handle events. You’ll then delve into Redux for state management and build amazing UI designs. With the help of practical solutions, this book will guide you in testing, debugging, and scaling your web applications, and get to grips with web technologies like WebPack, Node, and Firebase to develop web APIs and implement SSR capabilities in your apps. Before you wrap up, the recipes on React Native and React VR will assist you in exploring mobile development with React.By the end of the book, you will have become familiar with all the essential tools and best practices required to build efficient solutions on the web with React.
Data Wrangling with Python. Creating actionable data from raw sources
Dr. Tirthajyoti Sarkar, Shubhadeep Roychowdhury
For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain.The book starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The book will further help you grasp concepts through real-world examples and datasets.By the end of this book, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.
Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand.This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use.By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away.
While Apache Spark 1.x gained a lot of traction and adoption in the early years, Spark 2.x delivers notable improvements in the areas of API, schema awareness, Performance, Structured Streaming, and simplifying building blocks to build better, faster, smarter, and more accessible big data applications. This book uncovers all these features in the form of structured recipes to analyze and mature large and complex sets of data.Starting with installing and configuring Apache Spark with various cluster managers, you will learn to set up development environments. Further on, you will be introduced to working with RDDs, DataFrames and Datasets to operate on schema aware data, and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will also work through recipes on machine learning, including supervised learning, unsupervised learning & recommendation engines in Spark.Last but not least, the final few chapters delve deeper into the concepts of graph processing using GraphX, securing your implementations, cluster optimization, and troubleshooting.