At MentorCruise, we are all about making the most out of the experience of others. As part of that, we've connected and asked dozens of experts and professionals about their favourite Data Science books – and here are the answers.
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Understanding the concepts of Data Science starts with understanding the fundamentals. On your way to mastery, it's crucial for you to understand how certain concepts were derived, and why things work like they do. Starting with these resources is the best way to do so.
These days, businesses are collecting massive amounts of data. But this data isn’t valuable until someone analyzes it to gain insights that can be used to make decisions. That’s why the US Bureau of Labor Statistics (BLS) predicts that the demand for data analysts will continue to grow for the rest of the decade.
Now, with Murach’s Python for Data Science as your guide, you’ll learn how to …
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Data Science with Python and Dask teaches you to build scalable projects that can handle massive datasets. After meeting the Dask framework, you'll analyze data in the NYC Parking Ticket database and use DataFrames to streamline your process.
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Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA cour…
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Here's what to expect in Data Science for Dummies: Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value. Includes coverage of big data frameworks and applications like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL.
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Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career.
The first book of its kind, The Kaggle Book assembles in o…
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Natural language processing (NLP) is a field that focuses on making natural human language usable by computer programs. NLTK, or Natural Language Toolkit, is a Python package that you can use for NLP.
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These books are not required for you to learn Data Science, but they are highly recommended for you to deepen your knowledge.
Statistical methods are a key part 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.
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R in data science is used to handle, store and analyze data. It can be used for data analysis and statistical modeling. R is an environment for statistical analysis. R has various statistical and graphical capabilities.
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For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.
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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.
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WMDs, or Weapons of Math Destruction, are mathematical algorithms that supposedly take human traits and quantify them, resulting in damaging effects and the perpetuation of bias against certain groups of people.
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Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks.
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You've got your basics in order – time to move on to some advanced and specialized concepts. Data Science is evolving every day, these books can help you master it.
In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society.
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This list is curated by MentorCruise and can include Amazon affiliate links. Have any other suggestions? Add here.
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