Hi all! Hope that everyone out there is staying safe and healthy given the current crisis. We’re certainly getting a bit stir-crazy here in our New York City shoebox, but are so looking forward to moving to Los Angeles in just a short six weeks. This week, I’ve been slightly crazed with interviews and applications as the job search gets more real (eek!!) so my weekly post is a bit shorter and less technical than the past several weeks.
In this post, I’ll be focusing on my quarantine reading recommendations! One of my favorite parts about the additional free time we’ve gained via the stay-at-home orders is the much-needed time to tackle some titles on my ever-growing reading list. Whether it’s a thought-provoking nonfiction read or a comforting novel, sometimes a book is all the comfort you need during an oftentimes isolating time. Below I’ll briefly summarize my favorities so far (organized by nonfiction and fiction sections), and list some of those I’m excited to get to in the coming weeks!
Nonfiction
Weapons of Mass Destruction by Cathy O’Neil
Little remains to be said that I did not cover in last week’s blog post. Cathy O’Neils provides an innovative, thought-provoking snapshot of the ways in which the dystopian futures we fear may already have their claws gripped onto our society. From insurance agencies to advertising scams, for-profit colleges to job applications, our machine learning algorithms, as smart as they may seem, learn from the biases of those who program them, and oftentimes remain incapable of attaining the feedback necessary to unlearn these discriminatory tendencies. O’Neil gives us a brief glimpse into the ways big data is changing our society for the worse, and provides two potential doors for our future, but she leaves it up to readers as to which we will choose.
Read the book summary below, and find this title on Barnes & Noble or Amazon:
We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we can get a job or a loan, how much we pay for health insurance—are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.
But as mathematician and data scientist Cathy O’Neil reveals, the mathematical models being used today are unregulated and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination—propping up the lucky, punishing the downtrodden, and undermining our democracy in the process. Welcome to the dark side of Big Data.
Naked Statistics by Charles Wheelan
Statistics can be argued as the backbone of data science, as well as of a range of other subfields in applied mathematics. Charles Wheelan’s Naked Statistics, preceded by Naked Economics and followed by Naked Money, provides an engaging version of key statistical concepts, an essential read for any data scientist or those in any discipline utilizing statistical research methodologies. Whether you’re a lifelong statistics lover, or even someone who despises the mere thought of statistics, this book manages to engage the entire range of readers, as Wheelan discusses concepts from innovative perspectives that will make you laugh and think about statistics in a new way. Needless to say, Naked Economics and Naked Money on my to-read list as well.
Read the book summary below, and find this title on Barnes & Noble and Amazon:
Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called “sexy.” From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.
For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.
And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.
The Hundred Page Machine Learning Book by Andriy Burkov
As mentioned in some of my previous blog posts, this book is a MUST-HAVE for all data scientists and machine learning engineers. How the author manages to squeeze so much concise, useful information into just over one hundred pages is beyond me, but this is always the first resource I go to with questions about how to tackle a data science problem or for more in-depth conceptual information about a topic. With an additional online resource database, this book is the gift that keeps on giving, as Burkov and his team continue to update the hub with tools, links, and readings that supplement the book’s original content. Though I feel I have barely scratched the surface of the book’s usability, I’m excited to keep it by my side throughout my data science journey, especially in these first steps into a new career (wherever that may be!).
Read the book summary below, and find this title on Barnes & Noble and Amazon:
As its title says, it’s the hundred-page machine learning book. It was written by an expert in machine learning holding a Ph.D. in Artificial Intelligence with almost two decades of industry experience in computer science and hands-on machine learning.
This is a unique book in many aspects. It is the first successful attempt to write an easy to read book on machine learning that isn’t afraid of using math. It’s also the first attempt to squeeze a wide range of machine learning topics in a systematic way and without loss in quality.
The book contains only those parts of the huge body of material on machine learning developed since the 1960s that have proven to have a significant practical value. A beginner in machine learning will find in this book just enough details to get a comfortable level of understanding of the field and start asking the right questions. Practitioners with experience will use this book as a collection of pointers to the directions of further self-improvement.
The book also comes in handy when brainstorming at the beginning of a project, when you try to answer the question whether a given technical or business problem is “machine-learnable” and, if yes, which techniques you should try to solve it.
The book comes with a wiki which contains pages that extend some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources. Thanks to the continuously updated wiki this book like a good wine keeps getting better after you buy it.
The Signal and the Noise: Why So Many Predictions Fail–but Some Don’t by Nate Silver
From the founder of FiveThirtyEight, next on my nonfiction reading list is The Signal and the Noise! I’ve heard rave reviews about this book in many other data scientist’s blog posts and I’m excited to tackle it in the coming weeks. At 560 pages, this one is a bit longer than most other popular nonfiction reads I have encountered and I’m eager to see what those additional pages hold. Hopefully I’ll be able to dedicate a bit of a blog post to reviewing the book in a few weeks - check back to see!
Read the book summary below, and find this title on Barnes & Noble and Amazon:
Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation’s foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight.
Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future.
In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball to global pandemics, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good—or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary—and dangerous—science.
Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise.
With everything from the health of the global economy to our ability to fight terrorism dependent on the quality of our predictions, Nate Silver’s insights are an essential read.
Fiction
A Little Life by Hanya Yanagihara
Wow. I truly do not know how this summarize this tomb of a novel. Much of the first weeks of quarantine were dedicated to finishing this novel, which I started on the road in Costa Rica back in February. Captivated by the author’s thorough and unreserved characterizations in the first hundred pages, I could not put this book down. With the risk of sounding dramatic, this book transformed my life and the way that I think about our movement from birth to death. This book will draw out emotions you did not know you held within yourself and leave you feeling overcome by the sheer magnitude of this little-yet-rather-humongous life captured within its eight-hundred thirty-two pages.
Read the book summary below, and find this title on Barnes & Noble and Amazon:
A Little Life follows four college classmates—broke, adrift, and buoyed only by their friendship and ambition—as they move to New York in search of fame and fortune. While their relationships, which are tinged by addiction, success, and pride, deepen over the decades, the men are held together by their devotion to the brilliant, enigmatic Jude, a man scarred by an unspeakable childhood trauma. A hymn to brotherly bonds and a masterful depiction of love in the twenty-first century, Hanya Yanagihara’s stunning novel is about the families we are born into, and those that we make for ourselves.
Station Eleven by Emily St. John Mandel
Written years before our current crisis, this books feels eerily like a fortune teller’s predicitions for the future, as its characters navigate a pandemic-torn world, twenty years after an aggressive flu caused the collapse of society. Sound familiar? Less than a hundred pages into the novel (yes, this is my current read!), I’m simulaneously eager and terrified to see the path that St. John Mandel will takes us on. While COVID-19 may not by the pandemic to ruin our society, might the next insurmountable one be waiting just around the corner…
The author’s next novel, The Glass Hotel, inspired by the Bernie Maddoff Ponzi scheme of 2009, arrived last month, and needless to say, I’m excited to check this one out as well :)
Read the book summary below, and find this title on Barnes & Noble and Amazon:
Kirsten Raymonde will never forget the night Arthur Leander, the famous Hollywood actor, had a heart attack on stage during a production of King Lear. That was the night when a devastating flu pandemic arrived in the city, and within weeks, civilization as we know it came to an end.
Twenty years later, Kirsten moves between the settlements of the altered world with a small troupe of actors and musicians. They call themselves The Traveling Symphony, and they have dedicated themselves to keeping the remnants of art and humanity alive. But when they arrive in St. Deborah by the Water, they encounter a violent prophet who will threaten the tiny band’s existence. And as the story takes off, moving back and forth in time, and vividly depicting life before and after the pandemic, the strange twist of fate that connects them all will be revealed.
Summary
My reading list is constantly growing! Even with quarantine-time, it seems I will never have enough time to tackle all the engaging, thought-provoking titles out there. That being said, if you’ve made it this far and have any to add to my list, please send them my way - I would love the recommendations!! :)
Stay safe and healthy out there y’all! Here’s to counting down the weeks that remain. Take care!