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The Art of Data Science

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Release : 2016-06-08
Genre : Business & Economics
Kind : eBook
Book Rating : 462/5 ( reviews)

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Book Synopsis The Art of Data Science by : Roger D. Peng

Download or read book The Art of Data Science written by Roger D. Peng. This book was released on 2016-06-08. Available in PDF, EPUB and Kindle. Book excerpt: "This book describes the process of analyzing data. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science."--Leanpub.com.

Communicating with Data

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Author :
Release : 2021
Genre : Mathematics
Kind : eBook
Book Rating : 741/5 ( reviews)

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Book Synopsis Communicating with Data by : Deborah Nolan

Download or read book Communicating with Data written by Deborah Nolan. This book was released on 2021. Available in PDF, EPUB and Kindle. Book excerpt: Communicating with Data aims to help students and researchers write about their insights in a way that is both compelling and faithful to the data.

Data Science for Beginners

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Release : 2021-02-09
Genre :
Kind : eBook
Book Rating : 997/5 ( reviews)

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Book Synopsis Data Science for Beginners by : Andrew Park

Download or read book Data Science for Beginners written by Andrew Park. This book was released on 2021-02-09. Available in PDF, EPUB and Kindle. Book excerpt: ★ 55% OFF for Bookstores! Now at $49.95 instead of $59.95! ★ Your Customers Will Never Stop To Use This Complete Guide! Did you know that according to Harvard Business Review the Data Scientist is the sexiest job of the 21st century? And for a reason! If "sexy" means having rare qualities that are much in demand, data scientists are already there. They are expensive to hire and, given the very competitive market for their services, difficult to retain. There simply aren't a lot of people with their combination of scientific background and computational and analytical skills. Data Science is all about transforming data into business value using math and algorithms. And needless to say, Python is the must-know programming language of the 21st century. If you are interested in coding and Data Science, then you must know Python to succeed in these industries! Data Science for Beginners is the perfect place to start learning everything you need to succeed. Contained within these four essential books are the methods, concepts, and important practical examples to help build your foundation for excelling at the discipline that is shaping the modern word. This bundle is perfect for programmers, software engineers, project managers and those who just want to keep up with technology. With these books in your hands, you will: ● Learn Python from scratch including the basic operations, how to install it, data structures and functions, and conditional loops ● Build upon the fundamentals with advanced techniques like Object-Oriented Programming (OOP), Inheritance, and Polymorphism ● Discover the importance of Data Science and how to use it in real-world situations ● Learn the 5 steps of Data Analysis so you can comprehend and analyze data sitting right in front of you ● Increase your income by learning a new, valuable skill that only a select handful of people take the time to learn ● Discover how companies can improve their business through practical examples and explanations ● And Much More! This bundle is essential for anyone who wants to study Data Science and learn how the world is moving to an open-source platform. Whether you are a software engineer or a project manager, jump to the next level by developing a data-driven approach and learning how to define a data-driven vision of your business! Order Your Copy of the Bundle and Let Your Customers Start Their New Career Path Today!

Data Science for Beginners

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Author :
Release : 2020-01-26
Genre :
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Data Science for Beginners by : Andrew Park

Download or read book Data Science for Beginners written by Andrew Park. This book was released on 2020-01-26. Available in PDF, EPUB and Kindle. Book excerpt: Master the world of Python, Data Analysis, Machine Learning and Data Science with this comprehensive 4-in-1 bundle. Do you want to learn more about the amazing world of Data Science? Or are you interested in becoming a Python geek? Then keep reading. Created with the beginner in mind, this powerful bundle delves into the fundamentals behind Python and Data Science, from basic code and concepts to complex Neural Networks and data manipulation. Inside, you'll discover everything you need to know to get started with Python and Data Science, and begin your journey to success! In book one, PYTHON FOR BEGINNERS, you will learn: How to install Python What are the different Python Data Types, Variables and Basic Operators Data Structures, Functions and Files Conditional and Loops in Python Object-Oriented Programming (OOP), Inheritance and Polymorphism Essential Programming Tools and Exception Handling An application to Decision Trees And Much More! In book two, PYTHON FOR DATA ANALYSIS, you will learn: What Data Analysis is all about and why businesses are investing in this sector The 5 steps of a Data Analysis Neural Network The 7 Python libraries that make Python one of the best choices for Data Analysis How Data Visualization and Matplotlib can help you to understand the data you are working with. Some of the main industries that are using data to improve their business with 14 real-world applications And Much More! In book three, PYTHON MACHINE LEARNING, you will learn: What is Machine Learning and how it is applied in real-world situations Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence Machine learning training models, Regression techniques and Linear Regression in Python How to use Lists and Modules in Python The 12 essential libraries for Machine Learning in Python Artificial Neural Networks And Much More! And in book four, PYTHON DATA SCIENCE, you will learn: What Data Science is all about and why so many companies are using it to give them a competitive edge. Why Python and how to use it to implement Data Science The main Data Structures & Object-Oriented Programming, Functions and Modules in Python with practical codes and exercises The 7 most important algorithms and models in Data Science Data Aggregation, Group Operations, Databases and Data in the Cloud 9 important Data Mining techniques in Data Science And So Much More! Whether you're a complete beginner or a programmer looking to improve his skillset, Data Science for Beginners is your all-in-one solution to mastering the world of Python and Data Science. Would you like to know more?Scroll Up and Click on the BUY NOW Button to Get Your Copy!

The Art and Science of Analyzing Software Data

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Author :
Release : 2015-09-02
Genre : Computers
Kind : eBook
Book Rating : 438/5 ( reviews)

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Book Synopsis The Art and Science of Analyzing Software Data by : Christian Bird

Download or read book The Art and Science of Analyzing Software Data written by Christian Bird. This book was released on 2015-09-02. Available in PDF, EPUB and Kindle. Book excerpt: The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. Presents best practices, hints, and tips to analyze data and apply tools in data science projects Presents research methods and case studies that have emerged over the past few years to further understanding of software data Shares stories from the trenches of successful data science initiatives in industry

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