practical-mlops-book
ML-For-Beginners
| practical-mlops-book | ML-For-Beginners | |
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| 1 | 34 | |
| 970 | 86,783 | |
| 1.9% | 1.5% | |
| 3.4 | 9.7 | |
| 3 months ago | 5 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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practical-mlops-book
ML-For-Beginners
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10 Best AI Engineering GitHub Repos to Build Real Systems
A beginner-friendly ML curriculum with practical examples and exercises you can actually finish. A solid starting point if you’re new to ML and want quick wins. Link: https://github.com/microsoft/ML-For-Beginners
- Microsoft's Open-Source ML Curriculum Is Best to Learn ML from Scratch
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Learn Machine Learning with these GitHub repositories
*Learn Machine Learning with these amazing GitHub repositories! *
1⃣ [ML for Beginners](https://github.com/microsoft/ML-For-Beginners) by Microsoft
- A股大涨 - FAV0周刊#016
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A-Share Market Surge - FAV0 Weekly #016
Free Machine Learning Courses from Microsoft
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Top Github repositories for 10+ programming languages
Machine learning 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
What are some alternatives?
Made-With-ML - Learn how to develop, deploy and iterate on production-grade ML applications.
Data-Science-For-Beginners - 10 Weeks, 20 Lessons, Data Science for All!
aws-ml-guide - [Video]AWS Certified Machine Learning-Specialty (ML-S) Guide
pycaret - An open-source, low-code machine learning library in Python
FFU_VSE_Masters_Thesis_ML_Credit_Risk_Modelling - Repository for my Master's Thesis "Application of Machine Learning Models within Credit Risk Modelling" at Faculty of Finance and Accounting, Prague University of Economics and Prague (FFÚ VŠE)
fory-benchmarks - Serialization Benchmarks for apache fory(previously fury) with other libraries