Learn to code with Python

Migrate from pandas and scikit-Learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools. Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and machine learning with PySpark. You will learn to translate Python code from pandas/scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular machine learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Na鴳e Bayes, and neural networks. After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary to apply these methods using

This full-color book will inspire you to start solving problems and creating cloud-based applications and games fast, even if you've never done it before. Not just friendly and easy, it's the first cloud development beginner's guide that puts you in control of your own learning, and empowers you to build unique programs to solve problems you care about. Microsoft and author Rob Miles have reinvented the introductory programmer's tutorial, reflecting deep research into how today's newcomers learn, and why other books fall short. This guide is packed with innovations, including its "Snaps" library of pre-built operations that are easy to combine your own unique programs, Cookie Cutter templates give you a flying start, and "Make Something Happen" projects help you build skills by creating your own programs. All example code is provided as a GitHub repository, and Miles's step by step instructions are replicated as screencast videos, hosted on YouTube and linked from the book's website. A

Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations. The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated. After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python. What You Will LearnUse Python and numerical computation to demonstrate the power of simulationChoose a paradigm to run a simulationDraw statistical insights from numerical experimentsKnow how simulation is used to solve real-world problems Who This Book Is ForEntry-level to mid-level Python developers from various backg

Augment your knowledge of Python with this entertaining learning guide, which features 100 exercises and programming puzzles and solutions. Python Challenges will help prepare you for your next exam or a job interview, and covers numerous practical topics such as strings, data structures, recursion, arrays, and more.Each topic is addressed in its own separate chapter, starting with an introduction to the basics and followed by 10 to 15 exercises of various degrees of difficulty, helping you to improve your programming skills effectively. Detailed sample solutions, including the algorithms used for all tasks, are included to maximize your understanding of each area. Author Michael Inden also describes alternative solutions and analyzes possible pitfalls and typical errors.Three appendices round out the book: the first covers the Python command line interpreter, which is often helpful for trying out the code snippets and examples in the book, followed by an overview of Pytest for unit te

運用國外常見的字彙家族概念，讓相同拼讀方式的單字可以一起學習，單字練習從辨識、拼讀、閱讀到聽寫，系統性地加深單字熟稔度，字彙量立即倍數成長。搭配字彙家族故事和閱讀理解練習，幫助學生從單字到閱讀，閱讀流暢度與素養有效提升。最後加上的讀者劇場劇本，將前面學過的故事內容，重新以劇本方式呈現，多元化的學習方式，讓學習更有趣味。This series of books teach the word families in a fun, engaging way with stories and activities. As teaching the young children, this will help students start the very beginning reading, especially get the sense of sounds and words. Each lesson covers a word family story and followed by exercises to help students to:1.recognize word patterns and common phonetic sounds; 2.build the vocabulary and improve spelling skills;3.learn to read and understand stories;4.enhance oral reading fluency and have fun!

Thistitle is a Pearson Global Edition. The editorial team at Pearson has workedclosely with educators around the world to include content which is especiallyrelevant to an international and diverse audience.For courses in computerprogramming.A user-friendly,code-intensive introduction to C programming with case studies introducing applicationsand system programming.C How to Program is a comprehensive introduction toprogramming in C. Like other texts of the Deitels How to Program series,the books modular presentation serves as a detailed, beginner source ofinformation for college students looking to embark on a career in coding, orinstructors and software-development professionals seeking to learn how toprogram with C. The signature Deitel live-code approach presents concepts inthe context of 142 fully working programs rather than incomplete snips of code.This gives students a chance to run each program as they study it and see howtheir learning applies to real-world programming scenari

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.