Programming Collective Intelligence

What Hacker News says

1. nmstokerNov 2025
   Reminds me of reading Programming Collective Intelligence by Toby Segaran, which inspired me with a range of things, like building search, recommenders, classifiers etc.
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2. max_Nov 2024
   It depends?

   1. Programming Philosophy?

   - The Unix Philosophy

   - 97 Things every programmer should know

   2. CS Fundamentals

   - The Elements of Computing Systems by Simon

   - Algorithms by Jeff Erickson

   3. Data Science

   - Programming Collective Intelligence by Toby Segaran

   - Deep Learning by Ian Goodfellow & Yoshua Bengio

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3. dmitryminkovskyJul 2021
   I've always wondered about this. I first read about this challenge in "Programming Collective Intelligence,"[0] the O'Reilly book from 2007 that drove me to become a professional programmer. It starts like this:

   > Netflix is an online DVD rental company that lets people choose movies to be sent to their homes, and makes recommendations based on the movies that customers have previously rented.

   It was a different and exciting time back then! I never finished that book but hope to some day... :)

   [0] https://www.oreilly.com/library/view/programming-collective-...

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4. disgruntledphd2Dec 2018
   Programming Collective Intelligence is a fantastic book. I literally couldn't believe how many cool things it has throughout it.

   It doesn't assume much prior knowledge and guides you gently through solving a bunch of data problems.

   No affiliation, but its a great book regardless of it being a bit old (code is easy to update, good explanations are timeless).

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5. mindcrimeNov 2018
   I understand. But if you're going to ask a community like this for help, it usually helps to show that you've done some leg-work of your own already. Otherwise you risk having your question come off as a variation of "do my homework for me".

   Saying "I read these 6 blog posts, and came up with these 3 ideas about how to start, but I'm not sure how to pick between them", for example, would be a question that people would generally be more motivated to respond to. YMMV of course.

   FWIW, to give you one concrete suggestion, the Programming Collective Intelligence book is pretty good.

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6. proofofstakeAug 2017
   > What maths must be understood to enable pursuit of either of the above fields?

   None.

   > Are there any seminal texts/courses/content which should be consumed before starting?

   No.

   You don't need to know binary to start being a programmer/developer either. Just start already. As long as you are not in charge of a medical diagnosis or financial model, you don't get any drawback in experimenting (and failing miserably).

   Assuming applied ML, the most difficult part will be the human-political business element of it: People not understanding your model or using its output correctly, bias, feedback loops, acquiring enough resources, etc. The more you can explain to them, without resorting to heavy maths, the better communicator you are.

   That said, it can't hurt to do Ng's Coursera course (a lot of top performers started out with this course). Learning from Data by Caltech's Abu-Mostafa goes very wide on machine learning. "Programming Collective Intelligence" is a, somewhat dated, good book.

   As for seminal texts, the field is too wide for this. A better bet is: Find a professor in the field you are interested in. Say "Deep Learning", you could have a look at LeCun, Hinton, Schmidhuber, Bengio, ... Now look at their PhD-students, their papers, their courses, their conference talks, their software, their current research. Basically become a student under the most authoritative professor in the subfield you can find and resonate with, without ever paying any university tuition or them knowing you exist. This is very possible these days.

   But by all means: Just start out. Machine learning is fun. Learning about dry 100 year old maths not so much. Make mistakes. Learn to detect and avoid overfit. Find out if you are passionate and curious about parts of the field, then the theory will come eventually. A lot of the time these questions seem to demand answers like: "You need a PhD-level understanding of mathematics" Just so your brain can go: "I am not good enough for this, so let's look at something easier". Don't use this as an excuse. Start making intelligent stuff. There are 16-year-olds on Kaggle routinely beating maths PhD's.

   Also remember that, despite the current trend of calling everything "AI", that AI is a very wide field, of which mathematics is only a small part. There is philosophy, linguistics, cognitive science, physics, neuroscience, psychology, computer science, robotics, logic, ... all these parts vary wildly in their prerequisite maths knowledge.

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