Data Scientists at Work
by Sebastian Gutierrez
Data Scientists at Work is a collection of interviews with sixteen of the world’s most influential and innovative data scientists from across the spectrum of this hot new profession. “Data scientist is the sexiest job in the 21st century,” according to the Harvard Business Review. By 2018, the United States will experience a shortage of 190,000 skilled data scientists, according to a McKinsey report.
Through incisive in-depth interviews, this book mines the what, how, and why of the practice of data science from the stories, ideas, shop talk, and forecasts of its preeminent practitioners across diverse industries: social network (Yann LeCun, Facebook); professional network (Daniel Tunkelang, LinkedIn); venture capital (Roger Ehrenberg, IA Ventures); enterprise cloud computing and neuroscience (Eric Jonas, formerly Salesforce.com); newspaper and media (Chris Wiggins, The New York Times); streaming television (Caitlin Smallwood, Netflix); music forecast (Victor Hu, Next Big Sound); strategic intelligence (Amy Heineike, Quid); environmental big data (André Karpištšenko, Planet OS); geospatial marketing intelligence (Jonathan Lenaghan, PlaceIQ); advertising (Claudia Perlich, Dstillery); fashion e-commerce (Anna Smith, Rent the Runway); specialty retail (Erin Shellman, Nordstrom); email marketing (John Foreman, MailChimp); predictive sales intelligence (Kira Radinsky, SalesPredict); and humanitarian nonprofit (Jake Porway, DataKind). The book features a stimulating foreword by Google’s Director of Research, Peter Norvig.
Each of these data scientists shares how he or she tailors the torrent-taming techniques of big data, data visualization, search, and statistics to specific jobs by dint of ingenuity, imagination, patience, and passion. Data Scientists at Work parts the curtain on the interviewees’ earliest data projects, how they became data scientists, their discoveries and surprises in working with data, their thoughts on the past, present, and future of the profession, their experiences of team collaboration within their organizations, and the insights they have gained as they get their hands dirty refining mountains of raw data into objects of commercial, scientific, and educational value for their organizations and clients.
Machine Learning for Hackers
by Drew Conway, John Myles White
If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.
Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.
- Develop a naïve Bayesian classifier to determine if an email is spam, based only on its text
- Use linear regression to predict the number of page views for the top 1,000 websites
- Learn optimization techniques by attempting to break a simple letter cipher
- Compare and contrast U.S. Senators statistically, based on their voting records
- Build a “whom to follow” recommendation system from Twitter data
Journal of a Novel
by John Steinbeck
Steinbeck’s letters were written on the left-hand pages of a notebook in which the facing pages would be filled with the test of East of Eden. They touched on many subjects—story arguments, trial flights of workmanship, concern for his sons.
Part autobiography, part writer’s workshop, these letters offer an illuminating perspective on Steinbeck’s creative process, and a fascinating glimpse of Steinbeck, the private man.
The New Machiavelli
by H. G. Wells
In a Free State
by V. S. Naipaul
In the beginning it is just a car trip through Africa. Two English people—Bobby, a civil servant with a guilty appetite for African boys, and Linda, a supercilious “compound wife”—are driving back to their enclave after a stay in the capital. But in between lies the landscape of an unnamed country whose squalor and ethnic bloodletting suggest Idi Amin’s Uganda. And the farther Naipaul’s protagonists travel into it, the more they find themselves crossing the line that separates privileged outsiders from horrified victims. Alongside this Conradian tour de force are four incisive portraits of men seeking liberation far from home. By turns funny and terrifying, sorrowful and unsparing, In A Free State is Naipaul at his best.