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Dumb question, but... Is AI and ML the same thing? I ask because I am seeing a lot of my ML peers claim to be AI experts with years of experience, even though the term AI wasn't really used at all until OpenAI got big.
he probably felt the need to prescribe dense theoretical books given his position. prbably look like a fraud if he recommended ' grokking machine learning on manning.com'
Dumb question, but... Is AI and ML the same thing? I ask because I am seeing a lot of my ML peers claim to be AI experts with years of experience, even though the term AI wasn't really used at all until OpenAI got big.
Early incarnations/uses of the term include what is now sometimes referred to as Good Old Fashioned AI (GOFAI), with such things as expert systems and ontological classification systems; these still technically fall under the umbrella of "AI". After GOFAI came other forms of technology, including the precursors to our current deep learning models, including much simpler and smaller neural networks. Again, these are still "AI", even if that's not what the public thinks when they hear the term.
See: https://en.wikipedia.org/wiki/GOFAI and https://en.wikipedia.org/wiki/Symbolic_artificial_intelligen...
he probably felt the need to prescribe dense theoretical books given his position. prbably look like a fraud if he recommended ' grokking machine learning on manning.com'
‘Grokking’s description indicates it is for a very applied role: “teaches you how to apply ML to your projects using only standard Python code and high school-level math”.
The linked reading list appears to be targeted at one level up the stack so to speak. Instead of learning how to string a few Python libraries together (which is useful, not knocking it), the goal would possibly be writing the Python library itself for a ML architecture.
Given the author’s position, it makes sense why they found the content of the latter useful in getting to that position.
Dumb question, but... Is AI and ML the same thing? I ask because I am seeing a lot of my ML peers claim to be AI experts with years of experience, even though the term AI wasn't really used at all until OpenAI got big.
AI as a field has been around since the 50s and gone through multiple paradigms, but modern AI (since its resurgence around 2010) is effectively all machine learning.
Modern "publicly known and commercial" AI is effectively all machine learning
For a sample of non-ML AI that ML still has trouble solving, see papers published in:
I have read all of them and I have watched almost all of the training videos mentioned and that, is the list I would give anybody who I would want to discourage from joining the field. The textbooks I mean COME ON. They are comprehensive and neatly academic but not pragmatic at all. There are playlists in youtube that would cut through all the unnecessary content and will get you building RAG systems in a couple of h…
I've always wondered if Hugging Face is meant to evoke the feeling of being attacked by a Facehugger.