The Data Science Toolset
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Data Science
A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges. The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.
Data Science at the Command Line
Author: Jeroen Janssens
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2014-09-25
This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data. To get you started—whether you’re on Windows, OS X, or Linux—author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools. Discover why the command line is an agile, scalable, and extensible technology. Even if you’re already comfortable processing data with, say, Python or R, you’ll greatly improve your data science workflow by also leveraging the power of the command line. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on plain text, CSV, HTML/XML, and JSON Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow using Drake Create reusable tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines using GNU Parallel Model data with dimensionality reduction, clustering, regression, and classification algorithms
The Data Science Toolset
Unlock the ultimate guide to mastering the expansive world of data science with "The Data Science Toolset." Whether you're a curious beginner or a seasoned analyst, this eBook is your gateway to an arsenal of powerful tools and techniques designed to elevate your data analysis skills and transform the way you work with data. Dive into the essential aspects of data tool selection, from understanding your data requirements to conducting thorough cost-benefit analyses. Unleash the potential of Python with in-depth guidance on libraries like Pandas and NumPy, ensuring you can manipulate data with ease. Elevate your visualization game with advanced techniques using Matplotlib, Seaborn, and interactive Plotly plots. Learn to clean, wrangle, and transform data efficiently and explore R's robust ecosystem, from data manipulation and visualization with ggplot2 to sophisticated statistical modeling. Discover how SQL can be your ally in writing efficient queries and handling complex data operations. Automation awaits you as you delve into workflow tools and pipeline building with Apache Airflow and Luigi. Excel doesn't get left behind; unlock its potential with advanced functions, pivot tables, and powerful data transformation using Power Query. Venture into the world of machine learning, understanding algorithms and model deployment with practical tools like Flask and Docker. Time series analysis and NLP techniques open doors to predictive and text data analysis, while big data frameworks like Hadoop and Spark redefine what you can achieve with vast datasets. With a focus on ethics and privacy, this eBook ensures you maintain integrity and compliance throughout your data journey. Finally, sustain your growth by exploring ways to stay current in the field and expand your professional network. "The Data Science Toolset" is more than a book—it's your companion for navigating the ever-evolving landscape of data science, empowering you with the knowledge to succeed in this dynamic domain. Get ready to transform your data insights into impactful decisions.