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In 2010, I wrote my first line of code R at the University of Washington (UW), I began to realize that programming is more powerful than a spreadsheet. Over the past 10 years, "Data Science" is the word used more widely, there spate of big data, business intelligence, data analysis, and now the fire of artificial intelligence.
My major is "computational finance," the financial crisis are fresh in everyone's mind, for engineers, this is also very worthy of attention, if you want a high-paying job to enter the financial industry, to become a quantitative analyst, like today's data sciences.
Today's data scientists are often asked to learn a series of modeling techniques and methods. Such as linear regression, a lot of people are using it, but do not know how to use it, so there will be such a situation, a lot of new people are ready at any deployment model, but they do not understand the actual situation, these groups do not have the technical focus on solving the above technical blindness, but on the debate about what kind of tool selection (R or Python).
This article I will list a list of books, these books can help you stimulate questions about technical assumptions of the model before deploying to help you become more good data scientist.
This book is a portfolio of Nassim Taleb, his most famous book is "Black Swan" (I think the best is "anti-fragility" ) . Taleb is one of the greatest thinkers of our time. He was also a tweet spree, from his own experience, he has a variety of derivative financial instruments trading on the New York and London, and later became a philosopher of mathematics. You either love him or hate him, because he will continue to challenge your assumptions in all writing. If he wrote something, you should immediately put it out on your reading list.
This book tells the story of the birth of the early MIT Kelly formula, it is called the story behind the huge wealth. Through which you will learn about the origin of Claude Shannon and card scam father of information theory, and later became famous in Ed Thorpe (Ed Thorpe) of "Beat the Dealer" in. Thorpe is now regarded as the godfather of hedge funds quantified. Most importantly, this book shows a good model never be ignored, but bad model will make you crash . This story is the first time in history to solve a real-world computer science and mathematics cooperation (just for ××× ) . This story is a harbinger of scientific data in the industry 60 years ago, was born.
America's greatest bestselling science writer James Gleick fame as the author of the study course record in layman's language chaos, write a report on a literary illustrations. Due to non-linear process, many deep learning model is currently being developed and deployed can not be truly understood. This book will help you understand these limitations. In addition, a comprehensive review of Benoit Mandelbrot personal life and work to become a book of any data scientist must-read. James Gleick is an outstanding writer, many of his books are worth reading.
The book describes how technology has changed the stock market, and now, the prediction model is applied to the field of high-frequency trading, where decisions are made nanosecond speeds. This book describes the process of creating this hidden but powerful ecosystem. The magic of this story is that it tells the story of when you know some of the code, we can solve many problems, and make you understand and create real value is to do some really innovative things, rather than relying on existing assumptions. Sometimes you have to get a little crazy in order to solve a problem.
The book tells the story of a Bayesian formulation and Bayesian statistical theory of history and frequency, coupled with statistical history and review of key technical topics in plain language makes the book popular, through which you will learn about the history of Some thought the great figures such as Pierre Laplace and RA Fisher, and their philosophy of how to shape the data processing centuries.
This five books, while not exhaustive, but will help you handle the actual work issues, help you build a philosophical basis, in search of better techniques and models, not just some kind of mechanical application technology, we remember professional is priceless.
Author Isaac Faber: doctoral candidate at Stanford University, MatrixDS chief data scientist.
Original link: https: //towardsdatascience.com/five-books-every-data-scientist-should-read-that-are-not-about-data-science-f7335fb1f84f
The arrival of the Dragon Boat Festival, I hope these books will help you have a pleasant holiday ~
Recommended Reading || ||
https://mp.weixin.qq.com/s/ZcSfzHjxEd1lnWB4nitJ5A
https://mp.weixin.qq.com/s/QrNgOuG6E6ZVk-gayociWQ
By the Shanghai Municipal Economic and Information Technology Commission, Shanghai Municipal Commission of Commerce, the Shanghai Changning District People's Government guidance, Changning District, Shanghai Youth Federation, billion euros the company jointly organized the "2019 Annual Meeting of the new global economy - Industry Internet Summit" will be Shanghai Changning held.
The conference invited the HC Group, Oracle, spectacular network linking thousands of square science and technology, looking for steel, industry giants such as Jinshan Yun, Ming potential capital, capital afar, Alpha commune, STS line Internet industry fund industry investors . Internet industry practitioners and entrepreneurs to exchange participants will work together in the future of the Internet industry, then a total of industrial revolution new opportunities.
Assembly deadline June 13, the junior partner may be interested in "two-dimensional code scanning poster below" Or click on" read text " activities register and view the agenda of the General Assembly.
Event page link: https: //www.iyiou.com/a/cyhlw_shanghai_2019/
Scan poster dimensional code or click to read the original
A " Event Registration " and " View of the General Assembly agenda ."
Star I, every day a little more wisdom
Reproduced in: https: //blog.51cto.com/14143343/2405914