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Data Science from Scratch
This is a first-principles-based, practical introduction to the fundamentals of data science aimed at the mathematically-comfortable reader with some programming skills. The book covers: The important parts of Python to know The important parts of Math / Probability / Statistics to know The basics of data science How commonly-used data science techniques work (learning by implementing them) What is Map-Reduce and how to do it in Python Other applications such as NLP, Network Analysis, and more.
Your Religion Is False
The funniest book ever written about why your religion is false!Whether you're a Christian or a Jew, a Muslim or a Hindu, a Rasta or a Jain, an Environmentalist or a Cheondoist, a Scientologist or a Giant Stone Head Worshipper, your religion is false.But don't feel bad -- so is everyone else's! When you want to know what not to believe, this is the only book you need.In addition, you'll learn* Why "god" doesn't exist* Why there's no such thing as a "soul"* How to find "meaning" in a religion-less world* Which of your religious heroes are pedophiles* Why "religious tolerance" is a terrible ideaAnd, as a bonus, the greatest religious joke ever told. You can't afford not to read this book!
Thinking Spreadsheet
Whether you're a complete beginner or a grizzled veteran, Thinking Spreadsheet will make you an Excel expert. Its clear instruction and carefully-chosen examples will help you * Understand how spreadsheets work, what they do well, and what they don't do well. * Use the spreadsheet's structure to intelligently organize your data. * Solve problems using techniques that take advantage of the spreadsheet's strengths. * Build spreadsheets that are easy to understand and difficult to break. Along the way you'll learn core spreadsheet principles, basic tools like SUM() and IF(), advanced functions like MATCH() and VLOOKUP(), and power-user features like array formulas and pivot tables. You'll also learn a little bit of mathematics, a little bit of probability, a little bit of statistics, and a whole lot about how to intelligently solve problems. You might even laugh a few times!
Doing Data Science
Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an idea...
Hands On With Google Data Studio
Learn how to easily transform your data into engaging, interactive visual reports! Data is no longer the sole domain of tech professionals and scientists. Whether in our personal, business, or community lives, data is rapidly increasing in both importance and sheer volume. The ability to visualize all kinds of data is now within reach for anyone with a computer and an internet connection. Google Data Studio, quickly becoming the most popular free tool in data visualization, offers users a flexible, powerful way to transform private and public data into interactive knowledge that can be easily shared and understood. Hands On With Google Data Studio teaches you how to visualize your data today...
Data Wrangling with Python
How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that’s initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started. Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently. You’ll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain. Quickly learn basic Python syntax, data types, and language concepts Work with both machine-readable and human-consumable data Scrape websites and APIs to find a bounty of useful information Clean and format data to eliminate duplicates and errors in your datasets Learn when to standardize data and when to test and script data cleanup Explore and analyze your datasets with new Python libraries and techniques Use Python solutions to automate your entire data-wrangling process
Practical Statistics for Data Scientists
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why ...
Infinite Dimensional Analysis
This monograph presents a study of modern functional analysis. It is intended for the student or researcher who could benefit from functional analytic methods, but does not have an extensive background and does not plan to make a career as a functional analyst.
Data Science on the Google Cloud Platform
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you’ll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You’ll ...
Hands-On Data Science and Python Machine Learning
This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark. About This Book Take your first steps in the world of data science by understanding the tools and techniques of data analysis Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to ent...
