This is what has been added to DataSciGuide since 10/21/15:
- Broadening Participation in Data Mining – Our primary aim is to foster mentorship, guidance, and connections of minority and underrepresented groups in Data Mining, while also enriching technical aptitude and exposure.
- Creating a Data-Driven Organization – What do you need to become a data-driven organization? Far more than having big data or a crack team of unicorn data scientists, it requires establishing an effective, deeply-ingrained data culture.
- Data Science for Business: What you need to know about data mining and data-analytic thinking – Learn how to improve communication between business stakeholders and data scientists, and how to participate intelligently in your company’s data science projects. Discover how to think data-analytically, support business decision-making with data science methods.
- Data Science For Dummies – From uncovering rich data sources, to managing large amounts of data within hardware and software limitations, and beyond, you’ll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization.
- Freakonomics: A Rogue Economist Explores the Hidden Side of Everything – Which is more dangerous, a gun or a swimming pool? What do schoolteachers and sumo wrestlers have in common? How much do parents really matter?
- Moneyball – Moneyball is a quest for the secret of success in baseball and a tale of the search for new baseball knowledge—insights that will give the little guy who is willing to discard old wisdom the edge over big money.
- The Victory Lab: The Secret Science of Winning Campaigns – Armed with research from behavioral psychology and randomized experiments that treat voters as unwitting guinea pigs, the smartest campaigns now believe they know who you will vote for even before you do.
- Think Bayes – Use your existing programming skills to learn and understand Bayesian statistics. Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing.
- Thinking in Systems: A Primer – Some of the biggest problems facing the world―war, hunger, poverty, and environmental degradation―are essentially system failures. Thinking in Systems is a concise and crucial book offering insight for problem solving on scales ranging from the personal to the global.
- Visualize This: The FlowingData Guide to Design, Visualization, and Statistics – A common mistake in data design is to approach a project with a visual layout before looking at your data. This leads to graphics that lack context and provide little value. Explore what your data has to say first, and you can design graphics that mean something.
- What Is Data Science? – Why do we suddenly care about statistics and about data? This report examines the many sides of data science — the technologies, the companies and the unique skill sets.
Special thanks to my friend Sarah for helping me enter most of these items!
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