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THE VIDEO SHELF · machine learning fundamentals

Lecture 01 - The Learning Problem

The first lecture of Caltech's CS 156 Machine Learning course by Yaser Abu-Mostafa, introducing the learning problem and supervised, unsupervised and reinforcement learning. It is one of 18 lectures in the Learning from Data course.

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Why HN readers recommended it

Recommended repeatedly in 'where do I start with ML' threads as a clear, math-aware introduction.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
caltech
Topic
machine learning fundamentals
Format
course
Level
intro
HN recommenders in dataset
5
HN mentions in dataset
6
Recommendation years in dataset
2016–2023

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • I'm a neophyte to ML, but one course I very much enjoyed auditing was "Learning from Data" [1] taught by Caltech Professor Yaser Abu-Mostafa. I found concept of the _Learning Model_ particularly fresh representation of the ML activity (starting at 14:39 in the first video …

    xtiansimon on Hacker News · 2017-07
    In A Curated List of AI and Machine Learning Resources from Around the Web

  • I have found the Caltech machine learning intro course to be the most elucidating of any resource so far: [VIDEO] The delivery of the lecture material was like butter to me. Might work differently for others though.

    bob1029 on Hacker News · 2023-04
    In Ask HN: I am a full stack developer, where do I start learning for AI

  • there are some lectures about machine learning on youtube. I think they are good to watch: [VIDEO] and [LINK] and my favorite channels are Standford and MIT open courseware [LINK] and [LINK]

    weishigoname on Hacker News · 2016-10
    In Ask HN: What is your favorite YouTube channel for developers?

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.

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