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.
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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Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
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This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience. Determine the appropriate type of graph for your situation.
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Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do …
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Smarter Data Science outlines an effective and practical way for organizing, managing, and evaluating data, so you can establish an information architecture to better drive AI and data science. You'll learn how to: Simplify data management, making data available when and where it is needed.
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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.
This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks―scikit-learn and TensorFlow―author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems.
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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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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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Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee.
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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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