Here are 100 books that Predictive Analytics fans have personally recommended if you like
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I started my career as a research scientist building machine learning algorithms for weather forecasting. Twenty years later, I found myself at a precision agriculture startup creating models that provided guidance to farmers on when to plant, what to plant, etc. So, I am part of the movement from academia to industry. Now, at Google Cloud, my team builds cross-industry solutions and I see firsthand what our customers need in their data science teams. This set of books is what I suggest when a CTO asks how to upskill their workforce, or when a graduate student asks me how to break into the industry.
What if you are faced with a problem for which a standard approach doesn’t yet exist? In such a case, you will need to be able to figure out the approach from the first principles. This book will help you learn how to derive insights starting from raw data.
'A statistical national treasure' Jeremy Vine, BBC Radio 2
'Required reading for all politicians, journalists, medics and anyone who tries to influence people (or is influenced) by statistics. A tour de force' Popular Science
Do busier hospitals have higher survival rates? How many trees are there on the planet? Why do old men have big ears? David Spiegelhalter reveals the answers to these and many other questions - questions that can only be addressed using statistical science.
Statistics has played a leading role in our scientific understanding of the world for centuries, yet we are all familiar with the way…
I started my career as a research scientist building machine learning algorithms for weather forecasting. Twenty years later, I found myself at a precision agriculture startup creating models that provided guidance to farmers on when to plant, what to plant, etc. So, I am part of the movement from academia to industry. Now, at Google Cloud, my team builds cross-industry solutions and I see firsthand what our customers need in their data science teams. This set of books is what I suggest when a CTO asks how to upskill their workforce, or when a graduate student asks me how to break into the industry.
Even if you are ultimately going to be working with terabytes of data, you’ll start out doing exploratory data analysis. The tool that you’ll use for that is most likely going to be Pandas. One of the best investments that you can make when becoming a data scientist is to become a Pandas expert, and there is no better book than Harrison’s to help you get there. Plus, many of the interview questions you will face during the hiring process will probably involve Pandas. Blow your interviewers out of the water by showing them corners of the Pandas library they didn’t even know!
Best practices for manipulating data with Pandas. This book will arm you with years of knowledge and experience that are condensed into an easy to follow format. Rather than taking months reading blogs and websites and searching mailing lists and groups, this book will teach you how to write good Pandas code.
It covers:
Series manipulation
Creating columns
Summary statistics
Grouping, pivoting, and cross-tabulation
Time series data
Visualization
Chaining
Debugging code
and more...
I started my career as a research scientist building machine learning algorithms for weather forecasting. Twenty years later, I found myself at a precision agriculture startup creating models that provided guidance to farmers on when to plant, what to plant, etc. So, I am part of the movement from academia to industry. Now, at Google Cloud, my team builds cross-industry solutions and I see firsthand what our customers need in their data science teams. This set of books is what I suggest when a CTO asks how to upskill their workforce, or when a graduate student asks me how to break into the industry.
It is not enough for a data scientist to be able to analyze data and build ML models. You have to be able to communicate the insights to decision-makers concisely and accurately. This book shows you bad and good visualizations — you’ll be surprised by how often you would have defaulted to the bad way without the guidance provided by this book!
Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options.
This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke…
I started my career as a research scientist building machine learning algorithms for weather forecasting. Twenty years later, I found myself at a precision agriculture startup creating models that provided guidance to farmers on when to plant, what to plant, etc. So, I am part of the movement from academia to industry. Now, at Google Cloud, my team builds cross-industry solutions and I see firsthand what our customers need in their data science teams. This set of books is what I suggest when a CTO asks how to upskill their workforce, or when a graduate student asks me how to break into the industry.
In industry, your data is very likely to live within a data warehouse such as BigQuery, Redshift, or Snowflake. Therefore, to be an effective data scientist in the industry, you should learn how to use data warehouses effectively.
Once you learn data warehousing and SQL with any one of these products, it is quite easy to pick up another. So which one do you start with?
You can use Snowflake on all three of the major public clouds. Because it’s a standalone product, it is the most similar to a “traditional” data warehouse and can be picked up easily even if you are not familiar with cloud computing. That makes it a good data warehouse to start with, and is the reason my second book pick is this book on Snowflake.
BigQuery is also available on all three major public clouds, but it works best (and is used most commonly)…
Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud.
With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use.
Accurate and precise forecasting is essential for successful planning and policy from economics to epidemiology. We have been keen to understand why so many forecasts turn out to be highly inaccurate since making dreadful forecasts ourselves, and advising UK government agencies (Treasury, Parliament, Bank of England) during turbulent periods. As simple extrapolation often beats model-based forecasting, we have been developing improved methods that draw on the best aspects of both, and have published more than 60 articles and 6 books attracting more than 6000 citations by other scholars. Our recommended books cover a wide range of forecasting methods—suggesting there is no optimal way to look into the future.
This is a book that brings forecasters down to earth with a bang – we are not all super-forecasters! There is no magic involved in forecasting – seeing into the future is impossible. But Tetlock and Gardner show that good decision-making should be based on a set of guidelines that can be adapted to any situation. The writing is slick, given one of the authors is a science journalist, and it provides salutary reading for any would be practical forecaster.
'A manual for thinking clearly in an uncertain world. Read it.' Daniel Kahneman, author of Thinking, Fast and Slow _________________________ What if we could improve our ability to predict the future?
Everything we do involves forecasts about how the future will unfold. Whether buying a new house or changing job, designing a new product or getting married, our decisions are governed by implicit predictions of how things are likely to turn out. The problem is, we're not very good at it.
In a landmark, twenty-year study, Wharton professor Philip Tetlock showed that the average expert was only…
I'm Somi Arian, a tech philosopher, award-winning filmmaker, author, LinkedIn-Top-Voice, and the founder of InPeak, a Web3 education and professional networking platform. My background in Philosophy of Science and Technology informs my role in society as a 'Transition Architect.' My documentary, The Millennial Disruption, featuring industry leaders, won three international awards. My book, Career Fear (and how to beat it), addresses the future of work and the skills we all need to survive and thrive in the age of Artificial Intelligence and Blockchain. As a speaker, I give talks and workshops internationally on the impact of technology on society, the business landscape, the future of work, Web3, NFTs, the Metaverse, and blockchain technology.
This book is a prescient and compelling analysis of the challenges and opportunities presented by the transition from an industrial to an information-based society.
The authors, who have a track record of accurately predicting global political and economic trends, explore the shift towards a new era of individualized power, as governments lose their grip on commerce and society becomes more democratized.
They offer practical strategies for adapting financially to this new reality, emphasizing the importance of cultivating two skillsets in depth and becoming the best in your field to capitalize on the growing trend of personalized, online work.
The book covers a range of topics, including the mega political transformations in historic perspective, the sophistication of violence in the agricultural revolution, and the emergence of the cyber economy. It also delves into the impact of the information age on the global economy, government, and society, and explores the potential for…
Two renowned investment advisors and authors of the bestseller The Great Reckoning bring to light both currents of disaster and the potential for prosperity and renewal in the face of radical changes in human history as we move into the next century.
The Sovereign Individual details strategies necessary for adapting financially to the next phase of Western civilization.
Few observers of the late twentieth century have their fingers so presciently on the pulse of the global political and economic realignment ushering in the new millennium as do James Dale Davidson and Lord William Rees-Mogg. Their bold prediction of disaster on…
Everything in nature evolves by trial, error, and success—from fundamental physics, through evolution in biology, to how people learn, think, and decide.
This book presents a way of thinking and realistic knowledge that our formal education shuns. Stepping beyond this ignorance, the book shows how to deal with and even…
Since completing my PhD in political economy (dissertation: ‘International Integration and Foreign Policy Decision-making’) I have gone deeper into economic origins of change (eg. Modern Inflation, coauthored with well-known economist Wilhelm Hankel in Bologna, Italy at Johns Hopkins SAIS) and find the interactions between economic, politics, and psychology fascinating—presenting an infinite number of ‘Sherlock Holmes-like puzzles’. We are all now confronted with political, economic, and psychological uncertainties, put on high speed due to the war in Ukraine and great power tensions. So it is time to learn about the origins of our problems and their trends in order to better cope and find a basis for individual, if not collective, peace.
‘Dr. Doom’ (he prefers ‘Dr. Realist’) gives a lucid summary of major threats confronting the global economy and possible policy changes to alleviate them.
This book is well written and hits the nails all on the head with his diagnosis and possible corrective policies. HisYouTube interview on his book is brilliant, so I need not say more.
I grew up listening to my grandfathers tell stories about the Great Depression (1930s). My cousins would want me to go out and play, but I wanted to stay indoors and listen to the stories. The Depression proved my grandfathers were not the best cotton farmers, but they were good storytellers, and I ended up an economics professor. Along the way, I ran across a thought from renowned British philosopher Francis Bacon: “Histories make men wise, poets, witty, mathematics, subtle;” Modern economics has gone in for subtlety, and maybe is a little too careless of wisdom. This thought sent me delving deeper into economic history, and I ended up writing five books in economics history.
This book treats a rich variety of weighty topics, global in scope. It lays bare the real insights that bubble up when economic history is subpoenaed to the bar of economic thinking. The famous British Disraeli said he only read biographies because biographies were life without theory. It helps to take a break from scholars whose thoughts are pinned down by the most recent theories. To study economics without theory, it is necessary to study economic history. Economic forecasters too often have a bias toward predicting a continuation of existing trends with small adjustments. Rostov’s long sweep of history shows that these forecasts may be overridden by long-term trends. This book contains a lot of meat—a great abundance of instructive explanations, intelligent comments, and practical conclusions.
This monumental study is an account of the world economy from the eighteenth century to the twentieth, an analysis and prescription for the future, and a challenge to the neo-Keynesian theories of income determination and growth. It is based on some forty years of research and teaching.
Originally published in 1978, the volume looks back over the nineteenth and twentieth centuries. It includes an analysis of how the world's population expanded from about 1 billion in 1800 to 4 billion in 1976, with some 6.5 billion in sight for the year 2000; an account of the expansion and distribution of…
I found my passion for sustainable mobility while working on my PhD thesis about electric cars at a time when no one was interested in electric cars. I am fascinated by the disruptive forces in the transportation space. With my long-term work experience in management consulting, corporate, academics, and startups, I’m trying to make a contribution to making transport carbon-free.
This book shows how the future of our planet will be decided in Asia. It teaches us that when we aim to tackle climate change with impactful measures, it is not about America or Europe but about Asia.
With its tremendous size and growth in population, Asia will be the dominant continent in the world and therefore be key to solving the climate crisis.
Five billion people, two-thirds of the world's mega-cities, one-third of the global economy, two-thirds of global economic growth, thirty of the Fortune 100, six of the ten largest banks, eight of the ten largest armies, five nuclear powers, massive technological innovation, the newest crop of top-ranked universities. Asia is also the world's most ethnically, linguistically and culturally diverse region of the planet, eluding any remotely meaningful generalization beyond the geographic label itself. Even for Asians, Asia is dizzying to navigate.
Whether you gauge by demography, geography, economy or any other metric, Asia is already the present - and it is…
Accurate and precise forecasting is essential for successful planning and policy from economics to epidemiology. We have been keen to understand why so many forecasts turn out to be highly inaccurate since making dreadful forecasts ourselves, and advising UK government agencies (Treasury, Parliament, Bank of England) during turbulent periods. As simple extrapolation often beats model-based forecasting, we have been developing improved methods that draw on the best aspects of both, and have published more than 60 articles and 6 books attracting more than 6000 citations by other scholars. Our recommended books cover a wide range of forecasting methods—suggesting there is no optimal way to look into the future.
This is a readable tale of the rise of economic forecasters in the USA during the boom years of the 1920s, and their demise after failing to forecast the `Great Crash of 1929’ and ensuing Great Depression. Roger Babson did forewarn of a crash, but also failed after wrongly repeatedly forecasting an imminent recovery in the early 1930s. It holds many relevant lessons for our turbulent times, emphasizing that the future is always highly uncertain.
The period leading up to the Great Depression witnessed the rise of the economic forecasters, pioneers who sought to use the tools of science to predict the future, with the aim of profiting from their forecasts. This book chronicles the lives and careers of the men who defined this first wave of economic fortune tellers, men such as Roger Babson, Irving Fisher, John Moody, C. J. Bullock, and Warren Persons. They competed to sell their distinctive methods of prediction to investors and businesses, and thrived in the boom years that followed World War I. Yet, almost to a man, they…
