awesome-ai-residency
datascience
awesome-ai-residency | datascience | |
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7 | 4 | |
2,944 | 4,104 | |
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5.5 | 8.3 | |
4 months ago | 30 days ago | |
- | Creative Commons Zero v1.0 Universal |
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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.
datascience
- Datasciene Libraries for Python
- Datascience Libraries for Python
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Good resources for learning ML with time series in Python? Some links I've found, but looking for canonical resources.
This GitHub repo maintains a good list of resources. Check out the "Time Series" section. https://github.com/r0f1/datascience
- Opinionated List of Data Science Libraries for Python
What are some alternatives?
ai-jobs-net-salaries - A dataset of global salaries in AI/ML and Big Data.
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
machine-learning-for-software-engineers - A complete daily plan for studying to become a machine learning engineer.
mlnotify - 🔔 No need to keep checking your training - just one import line and you'll know the second it's done.
start-machine-learning - A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2024 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!
ml-visuals - 🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
awesome-bigdata - A curated list of awesome big data frameworks, ressources and other awesomeness.
Kats - Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
mlreef - The collaboration workspace for Machine Learning
darts - A python library for user-friendly forecasting and anomaly detection on time series.
awesome-production-machine-learning - A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning