course-nlp
deeplearning-notes
| course-nlp | deeplearning-notes | |
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| 11 | 71 | |
| 3,390 | 353 | |
| 0.0% | - | |
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| about 1 year ago | over 1 year ago | |
| Jupyter Notebook | ||
| - | MIT License |
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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
deeplearning-notes
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Intuition for LSTM cell structure
If you want in-depth understanding then I would recommend you to look for Deep Learning Specialization by Andrew Ng. (Course 4). He explained the LSTM and GRU cells in detail (mathematically). You can also find it on YouTube I guess. Hope it helps.
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[D] Best deep learning course?
Best place to get started https://www.coursera.org/specializations/deep-learning
- Which course from deeplearning.ai should I take first? There are so many now
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Where to go from here
I want to expand on what I learnt theory and practice to be able to complete a project, where I can download a video and run it through my model and it will be able highlight specified items, e.g people trees, cars. Will this course help me get there https://www.coursera.org/specializations/deep-learning
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This is my self-learning curriculum for ML. Hope it helps and open to feedback!
Another one from DeepLearning.ai and this is also the most popular course for Deep Learning and Neural Networks - https://www.coursera.org/specializations/deep-learning
- AI roadmap
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Assignments to practice for course "neural-networks-deep-learning"
This course is a part of one of the 5 courses in DL specialization: https://www.coursera.org/specializations/deep-learning. I am taking this course on Coursera where I have finished up to week 2. Now I need to practice for it, but I think I can't access assignments as its locked for paid viewers. Can someone share me the resources for practice or any alternatives you found useful?
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Coursera or Udacity for TF developer certificate
There is another [course] (https://www.coursera.org/specializations/deep-learning) by deeplearning ai that catched my eye and in review they say its more in detail than tf in practice course.
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Career in Computer Vision - Best way to spool up through OMSCS
Deep learning like others said, but I've seen some posts recommending taking an external class, like Andrew Ng's Coursera class https://www.coursera.org/specializations/deep-learning over the GT one. I haven't taken or plan on taking the GT one but some people found it lacking
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How relevant is “A super harsh guide to machine learning” for someone who is just tinkering with machine learning?
My recommendations are worth little, I'm just starting through all this stuff myself. I'm currently taking the Deep Learning specialization on Coursera and trying to map out what else I should be doing.
What are some alternatives?
eli5 - A library for debugging/inspecting machine learning classifiers and explaining their predictions
coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
argos-translate - Open-source offline translation library written in Python
Credit_Card_Data_Clustering - Using Gaussian Clustering and PCA Techniques to make clusters of the Credit Car data
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
Breast_Cancer_DecisionTree_Classifier
cornell-cs5785-2020-applied-ml - Teaching materials for the applied machine learning course at Cornell Tech (online edition)
ml-coursera-python-assignments - Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
nlp_course - YSDA course in Natural Language Processing
micrograd - A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
medspacy - Library for clinical NLP with spaCy.
NNfSiX - Neural Networks from Scratch in various programming languages