course-nlp
missing-semester
course-nlp | missing-semester | |
---|---|---|
11 | 375 | |
3,390 | 4,704 | |
0.0% | 1.1% | |
0.0 | 6.8 | |
about 1 year ago | 2 months ago | |
Jupyter Notebook | CSS | |
- | GNU General Public License v3.0 or later |
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course-nlp
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Need help finding good NLP course
fast.ai also has an NLP course.
- I got a crazy idea how about all the programs here work on making Ms.J a reality
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A simple and effective way to go from beginner to intermediate level of ML knowledge
fastai already has a course that covers traditional nlp as well
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Would I be better off with OMSCS or online self-learning?
My question: How do you think high-quality online resources such as https://missing.csail.mit.edu/, https://fullstackopen.com/en/, http://allendowney.github.io/ThinkBayes2/, https://www.fast.ai/2019/07/08/fastai-nlp/ compare to the online education from OMSCS? Do any of my reasons above ring false for you?
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Suggestions on My Learning Path
8 - Code-First Introduction to Natural Language Processing - fast.ai
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Ex-Googlers raise $40M to democratize natural-language AI
fast.ai are doing the best work democratizing AI (machine learning and neural networks), including natural language
Can't recommend the course enough and it's incredible that such a quality resource is available for essentially zero cost
https://github.com/fastai/course-nlp
https://www.youtube.com/playlist?list=PLtmWHNX-gukKocXQOkQju...
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Anyone have deep learning textbook recommendations, specifically focused on NLP?
fastai nlp course
- Good NLP Course
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Matrix Factorization Approaches to Topic Modeling
[1] Chapter on LSI from Introduction to Information Retrieval [2] A Code-First Approach to Natural Language Processing by fast.ai [3] Computational Linear Algebra by fast.ai [4] https://www.cc.gatech.edu/~hpark/papers/nmf_book_chapter.pdf
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OPEN SOURCE COMPUTER SCIENCE CURRICULUM
NLP
missing-semester
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Ask HN: I want to learn to use the terminal, where do I start
The missing semester of your cs education
https://missing.csail.mit.edu/
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Please advise, still struggling intensely
You mentioned having issues with accessory concepts so perhaps this might help: https://missing.csail.mit.edu/. There's also a chapter on git
- Curso del IPN
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CS2030S and CS2040S advice
https://missing.csail.mit.edu/ is a good way to pass the Dec-Jan break if you want to prep for CS2030S + some more general stuff.
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I cancelled my Replit subscription
Reflecting a little bit more I don't think it was replit's fault, per-say. But that change should have been made together with a larger adjustment to the program. Like adding a class/unit in the style of [the missing semester](https://missing.csail.mit.edu/) to make sure people came away with a good range of intuitions.
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Advice to a Novice Programmer
From MJD's post: I think CS curricula should have a class that focuses specifically on these issues, on the matter of how do you actually write software?
But they never do.
FWIW, MIT's "The Missing Semester of Your CS Education" attempts to deal with this lack, though, even there, it's an unofficial course taught between terms, during MIT's IAP -- Independent Activities Period[1] -- and not an actual CS course.
[0] https://missing.csail.mit.edu/
[1] https://en.wikipedia.org/wiki/Traditions_and_student_activit...
- School of SRE: Curriculum for onboarding non-traditional hires and new grads
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Advice / Resources from a "Seasoned Beginner"
Link to the "missing semester of your CS degree" course by MIT.
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MIT's Missing Semester Class: Beyond the CS Curriculum
Rightly called The Missing Semester (of Your CS Education), this class from MIT will teach you how to use some of the tools that are fundamental to the software engineering ecosystem. From shell scripting to the fundamentals of information security—spanning around 12 lectures—you can add a bunch of practical skills to your toolbox.
- ¿Recomendaciones sobre que aprender?
What are some alternatives?
deeplearning-notes - Notes for Deep Learning Specialization Courses led by Andrew Ng.
cs-topics - My personal curriculum covering basic CS topics. This might be useful for self-taught developers... A work in development! This might take a very long time to get finished!
eli5 - A library for debugging/inspecting machine learning classifiers and explaining their predictions
computer-science - :mortar_board: Path to a free self-taught education in Computer Science!
argos-translate - Open-source offline translation library written in Python
CS50x-2021 - 🎓 HarvardX: CS50 Introduction to Computer Science (CS50x)
ML-Workspace - 🛠All-in-one web-based IDE specialized for machine learning and data science.
vimrc - The ultimate Vim configuration (vimrc)
cornell-cs5785-2020-applied-ml - Teaching materials for the applied machine learning course at Cornell Tech (online edition)
javascript - JavaScript Style Guide
nlp_course - YSDA course in Natural Language Processing
materials - Bonus materials, exercises, and example projects for our Python tutorials