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Applied Natural Language Processing with Python

Applied Natural Language Processing with Python

by Taweh Beysolow II
150 Pages · 2018 · 2.9 MB · 1,122 Downloads · New!
" You miss 100% of the shots you don’t take. ” ― Wayne Gretzky
Advanced Analytics in Power BI with R and Python
by Ryan Wade
437 Pages · 2020 · 6.9 MB · 3,427 Downloads · New!
This easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field of data analytics to your work in Microsoft Power BI. Data analytics expert and author Ryan Wade shows you how to use R and Python to perform tasks that are extremely hard, if not impossible, to do using native Power BI tools. For example, you will learn to score Power BI data using custom data science models and powerful models from Microsoft Cognitive Services.
Advanced Data Analytics Using Python
by Sayan Mukhopadhyay
186 Pages · 2018 · 2.1 MB · 2,986 Downloads · New!
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Advanced Python Development
by Matthew Wilkes
627 Pages · 2020 · 7.9 MB · 2,611 Downloads · New!
This book builds on basic Python tutorials to explain various Python language features that aren’t routinely covered: from reusable console scripts that play double duty as micro-services by leveraging entry points, to using asyncio efficiently to collate data from a large number of sources. Along the way, it covers type-hint based linting, low-overhead testing and other automated quality checking to demonstrate a robust real-world development process.
An Introduction to Python and Computer Programming
by Yue Zhang
308 Pages · 2015 · 5.01 MB · 2,269 Downloads · New!
This book introduces Python programming language and fundamental concepts in algorithms and computing. Its target audience includes students and engineers with little or no background in programming, who need to master a practical programming language and learn the basic thinking in computer science/programming. The main contents come from lecture notes for engineering students from all disciplines, and has received high ratings. Its materials and ordering have been adjusted repeatedly according to classroom reception. Compared to alternative textbooks in the market, this book introduces the underlying Python implementation of number, string, list, tuple, dict, function, class, instance and module objects in a consistent and easy-to-understand way, making assignment, function definition, function call, mutability and binding environments understandable inside-out. By giving the abstraction of implementation mechanisms, this book builds a solid understanding of the Python programming language.
An Introduction to Statistics with Python
by Thomas Haslwanter
278 Pages · 2016 · 4.7 MB · 2,634 Downloads · New!
This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis.
Applied Reinforcement Learning with Python
by Beysolow II Taweh
168 Pages · 2019 · 3.4 MB · 4,006 Downloads · New!
Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym.