Data Smart
Using Data Science to Transform Information into Insight
by John W. Foreman · first published 2013
91% recommend9% neutral
Why HN recommends it
Teaches k-means, Naive Bayes, regression and optimization by working through practical problems in Excel, with almost no math notation. Suits beginners, non-coders and marketers who want to understand the methods.
Summarised by Claude from recommending comments
"Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions. But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope. Data science is little more than using straight-forward steps to process raw data into actionable insight. And
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…go, I really think it comes down to your preference/needs, and a good understanding of the data/related concepts often outweighs the differences among various tools. Look no further than John Foreman's "Data Smart": he does a beautiful job dissecting and analyzing a wide range of datasets with...Excel.
on “R beats Python, R beats Julia, Anyone else wanna challenge R?” ↗You can use Excel for more than many people think. For some great examples, and with only a single chapter at the end devoted to R, see Data Smart, by MailChimp's Chief Data Scientist: http://www.amazon.com/Data-Smart-Science-Transform-Informati...
on “Getting started in data science” ↗John Foreman's book _Data Smart_ follows the Excel-first methodology, and I've been appreciating how well this separates the data analysis from the toolset choice.
on “Please don't denigrate what a beginner is currently learning” ↗…for how to do hard things and how to do easy things, but not a lot for how to think of the hard things in terms of the easy things, and this falls in that category. Another good book on this topic is Data Smart by John Foreman, where he goes over basic data science skills in Excel.
on “R for Excel Users” ↗As a dumb marketer. I very much enjoyed John Foreman's Data Smart. https://www.goodreads.com/book/show/17682206-data-smart
on “Best Data Science Books According to the Experts” ↗I recently read a book called "Data Smart" [1], where the author does k-means and prediction algorithms literally in Excel. This was quite eye opening as the view to ML is not so enigmatic to enter. However, the translation of your data into…
on “Machine learning is easier than it looks” ↗…need to learn to do this stuff as a one-off and not as a career. That's why I wrote a book that teaches the algorithms with nearly no math notation while trying to be very rigorous: http://www.amazon.com/Data-Smart-Science-Transform-Informati...
on “Machine learning is easier than it looks” ↗If you want to learn the nitty-gritty of machine learning and optimization, I highly recommend his book, Data Smart: http://www.amazon.com/Data-Smart-Science-Transform-Informati... It's one of the few books on the subject that doesn't get bogged down with mathematical notation, nor does it cheat with "And Then A…
on “An Interview with John Foreman, Chief Data Scientist at MailChimp” ↗First of all, John Foreman is great. Read his book "Data Smart" and http://analyticsmadeskeezy.com/blog/ (disclaimer: I am in no way tied to John Foreman. Also, I work at a company that provides a data processing/collaboration SaaS...for big data! http://www.treasuredata.com)…
on “Surviving Data Science at the Speed of Hype” ↗…thorough explanation of concepts (as opposed to the 'black box' 'use this library' approach taken by many tutorials I've seen) then I highly recommend John Foreman's (Data Scientist at MailChimp) book "Data Smart". He implements algorithms on practical problems in Excel. I know that may sound off-putting but it's so much easier to visualise what's going on when you can see vectors of data change in a spreadsheet…
on “Using naive Bayes to predict movie review sentiment” ↗Thanks to John Foreman's book "Data Smart" I now regularly test small-scale machine learning problems in Excel. Sure, a developer will translate the end result to scikit-learn or AzureML, but this is stuff that's easily available to even mildly-technical…
on “What Is Code?” ↗Can't answer whether to learn R or Julia, but for a more general education on Data Science, this book might be a really good fit for you: Data Smart: Using Data Science to Transform Information into Insight https://www.amazon.com/Data-Smart-Science-Transform-Informat... All the work is done in Excel. I enjoyed the book quite a bit. Author is Chief…
on “A Look at How Traders and Economists Are Using the Julia Programming Language” ↗If you want to know the answer, check out Data Smart[1] It's a book about doing data science using Excel, until it doesn't make sense using Excel anymore. KMeans, Naive Bayes, Regression, etc. all in Excel, without totally abusing it. [1] https://www.amazon.com/Data-Smart-Science-Transform-Informat...
on “Show HN: Gridmaster – A Code School for Learning Spreadsheets” ↗The first chapter of "Data Smart" (https://www.amazon.ca/Data-Smart-Science-Transform-Informati...) gets into some more advanced but practical tasks in Excel. The material is accessible to the beginner and assumes little prior knowledge…
on “Ask HN: Best way/resources to learn Excel?” ↗As others have noted, many data scientists work in Excel. This book, which teaches data science, does just that: "Data Smart: Using Data Science to Transform Information into Insight" by by John W. Foreman https://www.amazon.com/Data-Smart-Science-Transform-Informat... This is likely the quickest way to start.
on “Ask HN: Am I too late for the “Data Science” wave?” ↗