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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.
Ripple Quick Start Guide. Get started with XRP and develop applications on Ripple's blockchain
This book starts by giving you an understanding of the basics of blockchain and the Ripple protocol. You will then get some hands-on experience of working with XRP.You will learn how to set up a Ripple wallet and see how seamlessly you can transfer money abroad. You will learn about different types of wallets through which you can store and transact XRP, along with the security precautions you need to take to keep your money safe.Since Ripple is currency agnostic, it can enable the transfer of value in USD, EUR, and any other currency. You can even transfer digital assets using Ripple. You will see how you can pay an international merchant with their own native currency and how Ripple can exchange it on the ?y. Once you understand the applications of Ripple, you will learn how to create a conditionally-held escrow using the Ripple API, and how to send and cash checks.Finally, you will also understand the common misconceptions people have about Ripple and discover the potential risks you must consider before making investment decisions.By the end of this book, you will have a solid foundation for working with Ripple's blockchain. Using it, you will be able to solve problems caused by traditional systems in your respective industry.
Tkinter is a modular, cross-platform application development toolkit for Python. When developing GUI-rich applications, the most important choices are which programming language(s) and which GUI framework to use. Python and Tkinter prove to be a great combination. This book will get you familiar with Tkinter by having you create fun and interactive projects. These projects have varying degrees of complexity. We'll start with a simple project, where you'll learn the fundamentals of GUI programming and the basics of working with a Tkinter application. After getting the basics right, we'll move on to creating a project of slightly increased complexity, such as a highly customizable Python editor. In the next project, we'll crank up the complexity level to create an instant messaging app. Toward the end, we'll discuss various ways of packaging our applications so that they can be shared and installed on other machines without the user having to learn how to install and run Python programs.
ESP8266 Internet of Things Cookbook. Over 50 recipes to help you master the ESP8266's functionality
The ESP8266 Wi-Fi Module is a self contained System on Chip (SOC) with an integrated TCP/IP protocol stack and can give any microcontroller access to your Wi-Fi network. It is capable of either hosting an application or offloading all Wi-Fi networking functions from another application processor.This book contains practical recipes that will help you master all ESP8266 functionalities. You will start by configuring and customizing the chip in line with your requirements. Then you will focus on core topics such as on-board processing, sensors, GPIOs, programming, networking, integration with external components, and so on. We will also teach you how to leverage Arduino using the ESP8266 and you'll learn about its libraries, file system, OTA updates, and so on. The book also provide recipes on web servers, testing, connecting with the cloud, and troubleshooting techniques. Programming aspects include MicroPython and how to leverage it to get started with the ESP8266. Towards the end, we will use these concepts and create an interesting project (IOT).By the end of the book, readers will be proficient enough to use the ESP8266 board efficiently.
Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In this second edition of Mastering Python Networking, you’ll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This book begins by reviewing the basics of Python and teaches you how Python can interact with both legacy and API-enabled network devices. As you make your way through the chapters, you will then learn to leverage high-level Python packages and frameworks to perform network engineering tasks for automation, monitoring, management, and enhanced security. In the concluding chapters, you will use Jenkins for continuous network integration as well as testing tools to verify your network. By the end of this book, you will be able to perform all networking tasks with ease using Python.
Saif Ahmed, Quan Hua, Shams Ul Azeem
Google's TensorFlow is a game changer in the world of machine learning. It has made machine learning faster, simpler, and more accessible than ever before. This book will teach you how to easily get started with machine learning using the power of Python and TensorFlow 1.x. Firstly, you’ll cover the basic installation procedure and explore the capabilities of TensorFlow 1.x. This is followed by training and running the first classifier, and coverage of the unique features of the library including data ?ow graphs, training, and the visualization of performance with TensorBoard—all within an example-rich context using problems from multiple industries. You’ll be able to further explore text and image analysis, and be introduced to CNN models and their setup in TensorFlow 1.x. Next, you’ll implement a complete real-life production system from training to serving a deep learning model. As you advance you’ll learn about Amazon Web Services (AWS) and create a deep neural network to solve a video action recognition problem. Lastly, you’ll convert the Caffe model to TensorFlow and be introduced to the high-level TensorFlow library, TensorFlow-Slim.By the end of this book, you will be geared up to take on any challenges of implementing TensorFlow 1.x in your machine learning environment.
Java Data Science Cookbook. Explore the power of MLlib, DL4j, Weka, and more
If you are looking to build data sciencemodels that are good for production,Java has come to the rescue. With the aidof strong libraries such as MLlib, Weka,DL4j, and more, you can efficientlyperform all the data science tasks youneed to.This unique book provides modernrecipes to solve your common andnot-so-common data science-relatedproblems. We start with recipes to helpyou obtain, clean, index, and search data.Then you will learn a variety of techniquesto analyze, learn from, and retrieveinformation from data. You will alsounderstand how to handle big data, learndeeply from data, and visualize data.Finally, you will work through uniquerecipes that solve your problems whiletaking data science to production, writingdistributed data science applications,and much more - things that will come inhandy at work.
This book uses Python as its computational tool. Since Python is free, any school ororganization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance.The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory,options and futures.This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM’s market risk,running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.