start-machine-learning
awesome-ai-residency
| start-machine-learning | awesome-ai-residency | |
|---|---|---|
| 45 | 7 | |
| 4,115 | 2,944 | |
| - | - | |
| 5.8 | 5.5 | |
| 21 days ago | 4 months ago | |
| MIT License | - |
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start-machine-learning
- Can anyone provide me a roadmap for learning AI and Data science?
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Is it Possible to Work in AI without a Formal Degree in Computer Science?
Yes, I mean the second. What technologies do you use and what's your mansion? Then I found this repository on GitHub https://github.com/louisfb01/start-machine-learning, should it be a good roadmap to follow in your opinion?
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Suggestions for my future(Long Post)
Someone posted this a year ago but must have updated it for 2023.
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I want to learn Artificial Intelligence from beginning.
AI learning roadmap
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Start learning the basics of AI and ML now.
For anyone wanting to dive and have no idea where to start, someone posted this to a programming sub a while ago and I bookmarked it.
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Any path to learn?
Hi, we have a guide in our community we share for this full of free learning resources online: https://github.com/louisfb01/start-machine-learning
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A friendly approach to ML (2022-just updated)!
The guide: https://www.louisbouchard.ai/learnai/ GitHub repo: https://github.com/louisfb01/start-machine-learning
- A Complete Roadmap for learning Machine Learning with many valuable resources + staying up-to-date with the news. Intended for anyone having zero or a small background in programming, maths, and machine learning.
awesome-ai-residency
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ML Research New Grad
For bachelors, AI residency programs may be a good (though competitive) choice. https://github.com/dangkhoasdc/awesome-ai-residency
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GaTech MSCS - it's crap
MSCS students are not expected to do independent research at GT. They are expected to assist Ph.D. students. This reflects poorly when applying for graduate school. Therefore, you **must** go for a pre-doc program instead of GT. List - https://github.com/dangkhoasdc/awesome-ai-residency
- Wrong fit for quant?
- GitHub - List of AI Residency Programs
- [D] What makes you an extremely competitive applicant for a top-tier US AI/ML master program?
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[D] Internship after ML phd?
Usually in order to be an intern at a big company, they would ask for some proof that you are still a student (but I would check it with the company). Maybe a one year AI residency would be more suitable in your case (https://github.com/dangkhoasdc/awesome-ai-residency)
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How do I transition to AI research? (I have an MS in Physics)
There are specific programs for people like you: AI residencies. These are intended as fast-track programs to get people from other fields up to speed in AI research. I have no personal experience with them though, and would expect the application process to be extremely competitive. Essentially all of the large AI players have such programs: Google, Microsoft, OpenAI, NVidia, Intel, IBM, Facebook... just google (or duckduckgo) "AI residency + [company name]". They all have different entry requirements / preferred qualifications. Check out, e.g., this guidance. Here is another residency link list and here are some pointers on how to prepare for an application.
What are some alternatives?
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
ai-jobs-net-salaries - A dataset of global salaries in AI/ML and Big Data.
PES-2021-Cheat-Table - Cheat Table for eFootball PES 2021
machine-learning-for-software-engineers - A complete daily plan for studying to become a machine learning engineer.
learn-monogame.github.io - Documentation to learn MonoGame from the ground up.
ml-visuals - 🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
yt-channels-DS-AI-ML-CS - A comprehensive list of 180+ YouTube Channels for Data Science, Data Engineering, Machine Learning, Deep learning, Computer Science, programming, software engineering, etc.
audio-ai-timeline - A timeline of the latest AI models for audio generation, starting in 2023!
nexify.io - Develop your skills with programming courses, explained step by step, to learn by building things.
human-memory - Course materials for Dartmouth course: Human Memory (PSYC 51.09)
python-awesome - Learn Python, Easy to learn, Awesome
ABigSurvey - A collection of 1000+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML).