What people recommend, in their own words, with the receipt.
Research scientist at Meta in Berlin working on multilingual models and evaluation; previously led the multilingual team at Cohere and was a research scientist at Google DeepMind.
6 things
Deep LearningBook Ian Goodfellow, Yoshua Bengio, Aaron Courville
Read the Deep Learning book. It is available as a pdf or on Amazon .
His site's FAQ page answering "What resources should I use to get started with Deep Learning?" (undated page; date is the earliest evidence available, the current copy). (undated page)
Speech and Language Processing, 2nd EditionBook Daniel Jurafsky and James H. Martin
If you're serious about learning NLP, I would recommend to study the fundamentals first by reading Speech and Language Processing, 2nd Edition by Jurafsky and Martin .
His site's FAQ page answering "What resources should I use to get started with Natural Language Processing (NLP)?" (undated page; date is the current copy). (undated page)
Machine Learning (Coursera)Course Andrew Ng
If you're new to Machine Learning, take the Coursera Machine Learning course by Andrew Ng .
His site's FAQ page answering "What resources should I use to get started with Deep Learning?" (undated page; date is the current copy). (undated page)
fast.ai Deep Learning coursesCourse fast.ai
In terms of Deep Learning online courses, take the courses offered by fast.ai .
His site's FAQ page answering "What resources should I use to get started with Deep Learning?" (undated page; date is the current copy). (undated page)
fast.ai NLP courseCourse fast.ai
A great practical and code-first introduction to NLP is the fast.ai NLP course .
His site's FAQ page answering "What resources should I use to get started with Natural Language Processing (NLP)?" (undated page; date is the current copy). (undated page)
Ghost (blogging platform, with GitHub Pages)Software Ghost
I am using Ghost with GitHub Pages , which has worked for me but requires some maintenance.
His site's FAQ page answering "What service or template should I use for starting a blog?" (undated page; date is the current copy). (undated page)
Every entry is a verbatim quote and a link to the public post it came from. Nothing is paraphrased. If it is not on record somewhere public, it is not here.
The verdict is what they actually said: loved and liked are explicit; recommended means they told others to get it; uses means they only say they use it; read is a book on their public shelf with no verdict; mixed and disliked are kept too.
A dashed affiliate link, sponsored or their own label means the post disclosed a relationship. It is shown, never hidden.
The small bar beside a date shows how dated a recommendation is for its kind of thing.
The bar shows how dated a recommendation is, for its kind of thing. Full and green is recent. It drains, and turns amber and then grey, as the post gets older.
What counts as old depends on the thing. A laptop praised four years ago has been replaced twice; a book loved twenty years ago is probably still loved. The bar is empty after about:
A striped bar means the post carries no date and the date shown is an estimate. No date at all, no bar.