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Introduction To Python For The Computer And Data Sciences

Introduction to Python for the Computer and Data Sciences PDF
Author: Paul Deitel
Publisher: Pearson
Release: 2019-02-15
Size: 50.14 MB
Format: PDF, Mobi
Category : Python (Computer program language)
Languages : en
Pages : 880
View: 1194

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For introductory-level Python programming and/or data-science courses. A groundbreaking, flexible approach to computer science and data science The Deitels' Introduction to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud offers a unique approach to teaching introductory Python programming, appropriate for both computer-science and data-science audiences. Providing the most current coverage of topics and applications, the book is paired with extensive traditional supplements as well as Jupyter Notebooks supplements. Real-world datasets and artificial-intelligence technologies allow students to work on projects making a difference in business, industry, government and academia. Hundreds of examples, exercises, projects (EEPs), and implementation case studies give students an engaging, challenging and entertaining introduction to Python programming and hands-on data science. The book's modular architecture enables instructors to conveniently adapt the text to a wide range of computer-science and data-science courses offered to audiences drawn from many majors. Computer-science instructors can integrate as much or as little data-science and artificial-intelligence topics as they'd like, and data-science instructors can integrate as much or as little Python as they'd like. The book aligns with the latest ACM/IEEE CS-and-related computing curriculum initiatives and with the Data Science Undergraduate Curriculum Proposal sponsored by the National Science Foundation.

Python Programming

Python Programming PDF
Author: John M. Zelle
Publisher: Franklin, Beedle & Associates, Inc.
Release: 2004
Size: 10.17 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 517
View: 165

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This book is suitable for use in a university-level first course in computing (CS1), as well as the increasingly popular course known as CS0. It is difficult for many students to master basic concepts in computer science and programming. A large portion of the confusion can be blamed on the complexity of the tools and materials that are traditionally used to teach CS1 and CS2. This textbook was written with a single overarching goal: to present the core concepts of computer science as simply as possible without being simplistic.

Python For Beginners

Python for Beginners PDF
Author: Mark Wilson
Publisher:
Release: 2020-11-14
Size: 69.51 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 204
View: 2609

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In tоdау'ѕ workplace, Pуthоn trаіnіng is an іnсrеаѕіnglу іmроrtаnt раrt of a programmer's education. As a dynamic lаnguаgе whоѕе design рhіlоѕорhу rеvоlvеѕ аrоund rеаdаbіlіtу and conciseness, Pуthоn іѕ a рорulаr сhоісе fоr uѕе аѕ a scripting lаnguаgе. Lіkе оthеr іntеrрrеtаtіvе lаnguаgеѕ, it іѕ more flexible than соmріlеd lаnguаgеѕ, аnd іt can bе used tо tіе disparate ѕуѕtеmѕ tоgеthеr. Indeed, Python is a versatile lаnguаgе with mаnу applications іn grоwіng fіеldѕ. Fоr example, Python іѕ a рорulаr рrоgrаmmіng language fоr educational ѕоftwаrе. Raspberry Pi, thе ѕіnglе-bоаrd соmрutеr project fоr tеасhіng ѕtudеntѕ соmрutеr рrоgrаmmіng, uses Python as іtѕ рrіmаrу рrоgrаmmіng language. In addition, much оf thе ѕоftwаrе for thе One Laptop per Child XO іѕ wrіttеn in Pуthоn. At thе оthеr еnd оf the educational spectrum, Pуthоn іѕ аlѕо a very еffесtіvе language for scientific соmрutіng аnd mathematical ѕоftwаrе fоr theoretical mathematics. Aѕ еduсаtіоnаl ѕоftwаrе dеvеlорmеnt соntіnuеѕ tо grоw, Pуthоn will bесоmе a more аnd more іmроrtаnt lаnguаgе tо know. In аddіtіоn tо еduсаtіоnаl ѕоftwаrе, Python іѕ аlѕо a fаvоrеd lаnguаgе for use іn AI tаѕkѕ. Because Pуthоn іѕ a scripting language wіth rісh tеxt processing tools, mоdulе architecture, and syntax ѕіmрlісіtу, it is a natural сhоісе for аррlісаtіоnѕ іnvоlvіng nаturаl lаnguаgе processing. Prоgrаmѕ like Wоlfrаm Alpha and Sіrі are juѕt bеgіnnіng to penetrate thе еnd-uѕеr mаrkеt аnd mаnу such рrоgrаmѕ уеt to соmе wіll bе written іn Python. Start reading this wonderful book.

Python For Data Analysis

Python for Data Analysis PDF
Author: Jason Test
Publisher: Independently Published
Release: 2020-11-14
Size: 80.69 MB
Format: PDF, ePub
Category :
Languages : en
Pages : 238
View: 3608

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Master the best methods for PYTHON. Learn how to programming as a pro and get positive ROI in 7 days with data science and machine learning Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your business thanks to the web applications? If so, keep reading: this bundle book is for you! Today, thanks to computer programming and PYTHON we can work with sophisticated machines that can study human behavior and identify underlying human behavioral patterns. Scientists can predict effectively what products and services consumers are interested in. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. PYTHON FOR DATA ANALYSIS will introduce you many selected tips and breaking down the basics of coding. You will discover as a beginner the world of data science, machine learning and artificial intelligence. The description of each topic is crystal-clear and you can easily practice with related exercises. Examples and step-by-step guides will guide you during the code-writing learning process. The following list is just a tiny fraction of what you will learn in this bundle: PYTHON FOR DATA SCIENCE ✅ The basics of Python programming ✅ Differences among programming languages: Vba, SQL, R, Python ✅ 3 reasons why Python is fundamental for Data Science ✅ Introduction to some Python libraries like NumPy, Pandas, Matplotlib, ✅ Python design patterns ✅ 3 step system why Python is fundamental for Data Science ✅Optimal tools and techniques for data visualization ✅ Analysis of popular Python projects templates ✅ Game creation with Pyhton PYTHON CRASH COURSE ✅ A Proven Method to Write your First Program in 7 Days ✅ 3 Common Mistakes to Avoid when You Start Coding ✅ Fit Python Data Analysis to your business ✅ A Simple Strategy to Write Clean, Understandable and Flexible Codes ✅ The One Thing You Need to Debug your Codes in Python ✅ 5 Practical exercises to start programming ✅ 7 Most effective Machine Learning Algorithms Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Today is the best day to start programming like a pro. It's never too late to learn a coding language, whether you're 19 or 50! If you really wish to learn Python and master its language, please click the BUY NOW button.

Introduction To Python For Science And Engineering

Introduction to Python for Science and Engineering PDF
Author: David J. Pine
Publisher: CRC Press
Release: 2018-08-15
Size: 67.93 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 300
View: 4650

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This guide offers a rapid introduction to Python programming to anyone with no experience in programming, taking a careful and methodical approach to presenting the features available and their use for performing practical scientific and engineering tasks.

Introduction To Python Programming For Business And Social Science Applications

Introduction to Python Programming for Business and Social Science Applications PDF
Author: Frederick Kaefer
Publisher: SAGE Publications
Release: 2020-08-06
Size: 80.65 MB
Format: PDF, ePub
Category : Business & Economics
Languages : en
Pages : 392
View: 4802

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Would you like to gather big datasets, analyze them, and visualize the results, all in one program? If this describes you, then Introduction to Python Programming for Business and Social Science Applications is the book for you. Authors Frederick Kaefer and Paul Kaefer walk you through each step of the Python package installation and analysis process, with frequent exercises throughout so you can immediately try out the functions you’ve learned. Written in straightforward language for those with no programming background, this book will teach you how to use Python for your research and data analysis. Instead of teaching you the principles and practices of programming as a whole, this application-oriented text focuses on only what you need to know to research and answer social science questions. The text features two types of examples, one set from the General Social Survey and one set from a large taxi trip dataset from a major metropolitan area, to help readers understand the possibilities of working with Python. Chapters on installing and working within a programming environment, basic skills, and necessary commands will get you up and running quickly, while chapters on programming logic, data input and output, and data frames help you establish the basic framework for conducting analyses. Further chapters on web scraping, statistical analysis, machine learning, and data visualization help you apply your skills to your research. More advanced information on developing graphical user interfaces (GUIs) help you create functional data products using Python to inform general users of data who don’t work within Python. First there was IBM® SPSS®, then there was R, and now there′s Python. Statistical software is getting more aggressive - let authors Frederick Kaefer and Paul Kaefer help you tame it with Introduction to Python Programming for Business and Social Science Applications.

Python For R Users

Python for R Users PDF
Author: Ajay Ohri
Publisher: John Wiley & Sons
Release: 2017-11-13
Size: 62.50 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 368
View: 5982

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The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to code in Python and Python users to program in R. Short on theory and long on actionable analytics, it provides readers with a detailed comparative introduction and overview of both languages and features concise tutorials with command-by-command translations—complete with sample code—of R to Python and Python to R. Following an introduction to both languages, the author cuts to the chase with step-by-step coverage of the full range of pertinent programming features and functions, including data input, data inspection/data quality, data analysis, and data visualization. Statistical modeling, machine learning, and data mining—including supervised and unsupervised data mining methods—are treated in detail, as are time series forecasting, text mining, and natural language processing. • Features a quick-learning format with concise tutorials and actionable analytics • Provides command-by-command translations of R to Python and vice versa • Incorporates Python and R code throughout to make it easier for readers to compare and contrast features in both languages • Offers numerous comparative examples and applications in both programming languages • Designed for use for practitioners and students that know one language and want to learn the other • Supplies slides useful for teaching and learning either software on a companion website Python for R Users: A Data Science Approach is a valuable working resource for computer scientists and data scientists that know R and would like to learn Python or are familiar with Python and want to learn R. It also functions as textbook for students of computer science and statistics. A. Ohri is the founder of Decisionstats.com and currently works as a senior data scientist. He has advised multiple startups in analytics off-shoring, analytics services, and analytics education, as well as using social media to enhance buzz for analytics products. Mr. Ohri's research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces for cloud computing, investigating climate change and knowledge flows. His other books include R for Business Analytics and R for Cloud Computing.

Introduction To Data Science

Introduction to Data Science PDF
Author: Laura Igual
Publisher: Springer
Release: 2017-02-22
Size: 21.94 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 218
View: 2019

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This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.

Introduction To Data Science For Social And Policy Research

Introduction to Data Science for Social and Policy Research PDF
Author: Jose Manuel Magallanes Reyes
Publisher: Cambridge University Press
Release: 2017-09-21
Size: 12.91 MB
Format: PDF, ePub, Docs
Category : Social Science
Languages : en
Pages :
View: 149

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Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

Introduction To Machine Learning With Python

Introduction to Machine Learning with Python PDF
Author: Andreas C. Müller
Publisher: "O'Reilly Media, Inc."
Release: 2016-09-26
Size: 74.19 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 400
View: 4841

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Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you’ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills