# ML-Quant: Professional & Open Research **URL:** \ **Category:** Data Science\ **Created:** [January 12, 2022, 9:57pm UTC](https://forum.numer.ai/t/ml-quant-professional-open-research/4772 "2022-01-12T21:57:29Z")\ **Posts on this page:** 3\ **Page:** 1
**Author:** ![snowdere](https://avatars.discourse-cdn.com/v4/letter/s/5f8ce5/32.png) [@snowdere](https://forum.numer.ai/u/snowdere)\ **Post date:** [January 12, 2022, 9:57pm UTC](https://forum.numer.ai/t/ml-quant-professional-open-research/4772/1 "2022-01-12T21:57:29Z")
A couple of months ago I helped launch the Kaggle G-Research crypto competition, I have since thought about methods to obtain up-to-date research that could be used by participants to discover signals. The solution was [ML-Quant](https://www.ml-quant.com/), a public and free solution that will get you halfway there. So far the focus has been on academic literature (like ArXiv, SSRN, and RePec), and general media (Blogs, Podcasts, Videos). A few Numerai members have responded to my LinkedIn post, so I thought I would post it here for your feedback and recommendations. And would happily answer any question too! ![image](https://canada1.discourse-cdn.com/flex009/uploads/numerai/original/2X/4/49f4dc99604f6c1af9311c71116c807fc16630b0.png) ---
**Author:** ![kirua](https://yyz1.discourse-cdn.com/flex009/user_avatar/forum.numer.ai/kirua/32/1456_2.png) [@kirua](https://forum.numer.ai/u/kirua)\ **Post date:** [January 13, 2022, 10:23pm UTC](https://forum.numer.ai/t/ml-quant-professional-open-research/4772/2 "2022-01-13T22:23:53Z")
Saw it on reddit and using it sometimes mainly for the paper section. Appreciate the effort sir ^ ^ ---
**Author:** ![snowdere](https://avatars.discourse-cdn.com/v4/letter/s/5f8ce5/32.png) [@snowdere](https://forum.numer.ai/u/snowdere)\ **Post date:** [January 17, 2022, 10:56pm UTC](https://forum.numer.ai/t/ml-quant-professional-open-research/4772/3 "2022-01-17T22:56:20Z")
That is a pleasure @kirua, please let me know if you have any recommendations. 🙂