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It's hard to recommend something if we don't really know your level of knowledge so far. I wholeheartedly recommend the fast.ai [0] course. It provides a lot o

It's hard to recommend something if we don't really know your level of knowledge so far. I wholeheartedly recommend the fast.ai [0] course. It provides a lot of instantly applicable code, coupled with very good explanations which you can try out on novel problems later. It's focused on "learning by doing", and not "learning by reading" which fits my style really well. That said, it doesn't dissuade the watcher from reading later, it's just not recommended to start out with. [0]: course.fast.ai

bvc35 8y ago
So far I have taken one introductory class on AI in general, but it did not cover machine learning. I took one class on machine learning, but I only grasped the basics of several algorithms from the class. These classes, and the textbook I've partially completed, are the extent of my knowledge. Thank you for that suggestion.
- genericpseudo 8y ago
  Take as much probability and linear algebra as you can conveniently do – as much for the intuition as for the symbol-manipulation mechanics – and don't underrate the importance of domain expertise in any problem you get interested in!
corporateslaver 8y ago
More marketing from fast.ai on hn
- claytonjy 8y ago
  it seems weird to count "enthusiastic, uncompensated endorsement from satisfied customers" as "marketing"; maybe it is technically marketing, but it carries none of the negative connotation your comment seems to imply
  - barbecue_sauce 8y ago
    This guy consistently hates on people who suggest fast.ai as a resource, without giving any reasoning.
- rdrey 8y ago
  I've done Andrew Ng's Coursera specialization (deeplearning.ai) and course.fast.ai, and I would 100% recommend starting with fast.ai. (Seeing results more quickly is motivating. It's also free.) When you know that you enjoy the topic, feel free to learn more rigorous ML theory from other sources.
claytonjy 8y ago
I think this class/site is mentioned on every relevant HN for very good reason: it's actually that good. I dislike learning from video (upping playback speed helps), I dislike the coding style of the library and the notebooks (nonlinear notebook execution especially), and I still think this is the best available class on anything deep-learning related, and it's only getting better. The top-down, practice-before-theory approach is excellent, but they still get into the theory, often in a much more intuitive and better motivated way than you get elsewhere. Also tons of little breadcrumbs dropped throughout lessons and in the forum to dig deeper for those inclined to. If you go this route, make sure to follow the suggestion of re-implementing each lesson, from scratch, without referring back to the original notebook. It's a little too easy to not do that and miss out on the lessons you learn from struggling through the actual code.

bvc35 8y ago

So far I have taken one introductory class on AI in general, but it did not cover machine learning. I took one class on machine learning, but I only grasped the basics of several algorithms from the class. These classes, and the textbook I've partially completed, are the extent of my knowledge. Thank you for that suggestion.

genericpseudo 8y ago
Take as much probability and linear algebra as you can conveniently do – as much for the intuition as for the symbol-manipulation mechanics – and don't underrate the importance of domain expertise in any problem you get interested in!

corporateslaver 8y ago

More marketing from fast.ai on hn

claytonjy 8y ago
it seems weird to count "enthusiastic, uncompensated endorsement from satisfied customers" as "marketing"; maybe it is technically marketing, but it carries none of the negative connotation your comment seems to imply
- barbecue_sauce 8y ago
  This guy consistently hates on people who suggest fast.ai as a resource, without giving any reasoning.
rdrey 8y ago
I've done Andrew Ng's Coursera specialization (deeplearning.ai) and course.fast.ai, and I would 100% recommend starting with fast.ai. (Seeing results more quickly is motivating. It's also free.) When you know that you enjoy the topic, feel free to learn more rigorous ML theory from other sources.

claytonjy 8y ago

I think this class/site is mentioned on every relevant HN for very good reason: it's actually that good. I dislike learning from video (upping playback speed helps), I dislike the coding style of the library and the notebooks (nonlinear notebook execution especially), and I still think this is the best available class on anything deep-learning related, and it's only getting better. The top-down, practice-before-theory approach is excellent, but they still get into the theory, often in a much more intuitive and better motivated way than you get elsewhere. Also tons of little breadcrumbs dropped throughout lessons and in the forum to dig deeper for those inclined to. If you go this route, make sure to follow the suggestion of re-implementing each lesson, from scratch, without referring back to the original notebook. It's a little too easy to not do that and miss out on the lessons you learn from struggling through the actual code.