Understanding_the_EM_Algorithm
ML-For-Beginners
| Understanding_the_EM_Algorithm | ML-For-Beginners | |
|---|---|---|
| 1 | 28 | |
| 7 | 67,033 | |
| - | 2.6% | |
| 0.0 | 7.6 | |
| about 2 years ago | 4 days ago | |
| Jupyter Notebook | HTML | |
| MIT License | MIT License |
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Understanding_the_EM_Algorithm
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[D] My new blog post "Understanding the EM Algorithm"
The EM algorithm is very straightforward to understand with one or two proof-of-concept examples. However, if you really want to understand how it works, it may take a while to walk through the math. The purpose of this article is to establish a good intuition for you, while also provide the mathematical proofs for interested readers. The codes for all the examples mentioned in this article can be found at https://github.com/mistylight/Understanding_the_EM_Algorithm.
ML-For-Beginners
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Good coding groups for black women?
- https://github.com/microsoft/ML-For-Beginners
Also check out this list Pitt puts out every year:
- FLaNK Stack Weekly for 20 Nov 2023
- ML for Beginners GitHub
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is it worth learning NLP without master degree?
I don't recommend just jumping in into natural language processing directly without understanding artificial intelligence theory. I personally recommend for you to start with the basic stuff (regression, classification, and clustering, for example), and then jump into more advanced topics. You already know software developer stuff, so that's a big step already, and it should be easier to understand some concepts. Maybe follow Microsoft's machine learning for beginners curriculum? It looks like a good roadmap overall to not instantly burn out on nlp
- AI i Machine Learning
- I want to learn more about AI and Machine Learning
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Pocetak ML karijere
https://github.com/microsoft/ML-For-Beginners jel mislis na ovo?
- How could I have known
- GitHub - microsoft/ML-For-Beginners: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
- How do I reset my career after already getting my masters?
What are some alternatives?
azureml-examples - Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
pycaret - An open-source, low-code machine learning library in Python
Data-Science-For-Beginners - 10 Weeks, 20 Lessons, Data Science for All!
pyVHR - Python framework for Virtual Heart Rate
S2ML-Art-Generator - Multiple notebooks which allow the use of various machine learning methods to generate or modify multimedia content [Moved to: https://github.com/justin-bennington/S2ML-Generators]
amazon-denseclus - Clustering for mixed-type data
rmi - A learned index structure
ai-seed - 1000+ ready code templates to kickstart your next AI experiment
ML-Workspace - 🛠All-in-one web-based IDE specialized for machine learning and data science.
996.ICU - Repo for counting stars and contributing. Press F to pay respect to glorious developers.