Uploaded June 2021 | Updated September 2026, 53 minutes ago
After getting bad ML results, how to improve ML results is a common question. To get better ML results there are a number of points you can focus on. Improving your model is the obvious one, but there are also many other way to improve ML results (e.g. accuracy, recall, precision, f1 score). Methods include getting more data to assembling. There is no easy answer, but this video will hopefully give you somewhat of an idea of how to get starting with optimizing your Machine Learning approach.
After getting bad ML results, how to improve ML results is a common question. To get better ML results there are a number of points you can focus on. Improving your model is the obvious one, but there are also many other way to improve ML results (e.g. accuracy, recall, precision, f1 score). Methods include getting more data to assembling. There is no easy answer, but this video will hopefully give you somewhat of an idea of how to get starting with optimizing your Machine Learning approach.
![Research Collab Update [Zero to Paper]](https://i.ytimg.com/vi/57oTosh6jUQ/mqdefault.jpg "Research Collab Update [Zero to Paper]
Discord link: https://discord.gg/zZb6GmduR3
This is an update video for anyone that wants to work on the Zero to Paper project where we are doing novel ML research from scratch. This video provides instruction on how to help with the literature reviews and reading paper. Thank you so much for everyone that helps out with gathering research and summarizing all the Machine Learning research!
Zero to Paper playlist: https://www.youtube.com/watch?v=74fKCvr5n5o&list=PL_49VD9KwQ_ONxENRk11jFEI3_pqAwaug
RL Theory series if you want to get into RL: https://www.youtube.com/watch?v=1OI0uuz9jkI&list=PL_49VD9KwQ_OML1Knh-Yb7FUFkhTLS0jL")
