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firmai / repository
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
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We're seeking to collaborate with motivated, independent PhD graduates or doctoral students on approximately seven new projects in 2024. If you’re interested in contributing to cutting-edge investment insights and data analysis, please get in touch! This could be in colaboration with a university or as independent study.
Sov.ai is at the forefront of integrating advanced machine learning techniques with financial data analysis to revolutionize investment strategies. We are working with three of the top 10 quantitative hedge funds, and with many mid-sized and boutique firms.
Our platform leverages diverse data sources and innovative algorithms to deliver actionable insights that drive smarter investment decisions.
By joining Sov.ai, you'll be part of a dynamic research team dedicated to pushing the boundaries of what's possible in finance through technology. Before expressing your interest, please be aware that the research will be predominantly challenging and experimental in nature.
We offer a wide range of projects that cater to various interests and expertise within machine learning and finance. Some of the exciting recent projects include:
Please visit docs.sov.ai for more information on public projects that have made it into the subscription product. If you already have a corporate sponsor, we are also happy to work with them.
If you’re excited about leveraging your expertise in machine learning and finance to drive impactful research and projects, we’d love to hear from you! Please reach out to us at research@sov.ai with your resume and a brief description of your research interests.
Join us in shaping the future of investment insights and making a meaningful impact in the world of finance!
Have a look at the newly started FirmAI Medium publication where we have experts of AI in business, write about their topics of interest.
Please add your tools and notebooks to this Google Sheet. Or simply add it to this subreddit, r/datascienceproject
Highlight in YELLOW to get your package added, you can also just add it yourself with a pull request.
A curated list of applied machine learning and data science notebooks and libraries accross different industries. The code in this repository is in Python (primarily using jupyter notebooks) unless otherwise stated. The catalogue is inspired by awesome-machine-learning. r/datascienceproject is a subreddit where you can share all your data science projects.
Caution: This is a work in progress, please contribute, especially if you are a subject expert in any of the industries listed below. If you are a [analytical, computational, statistical, quantitive] researcher/analyst in field X or a field X [machine learning engineer, data scientist, modeler, programmer] then your contribution will be greatly appreciated.
If you want to contribute to this list (please do), send me a pull request or contact me @dereknow or on linkedin or get in contact on the website FirmAI. Also, a listed repository should be deprecated if:
Help Needed: If there is any contributors out there willing to help first populate and then maintain a Python analytics section in any one of the following sub/industries, please get in contact with me. Also contact me to add additional industries.
See data-science-career repo for more.
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