Hello. I am currently learning from the book “Deep Learning for the Life Sciences” and working towards implementing two papers from scratch. I will document everything I learn along the way in this post 
Paper 1: High-performance brain-to-text communication via handwriting [my implementation]
Paper 2: Large language models generate functional protein sequences across diverse families [my implementation]
The last two days i learned: how neurons communicate, how to identify toxic molecules in the human body (deep dive soon)
@bharath Could you please allow my account to add more than one image and link? I have a few study notes from the book. Thank you!!!
I believe that the forum sets permission levels automatically. As more people like/respond to your posts, you will gain permissions to link to more images. Good luck on your learning project!
the last two days i learned: the common types of brain responses in brain-computer interfaces, an overview of generating new proteins using language models (ProGen paper), how to go from DNA to proteins
the last four days i learned: 1/6 the decoder model for neural activity, how to handle neural representation change over time (will share notes after finishing it), more on brain responses used to control a BCI, and some biology
the last three days i learned: wrote dataset classes for character and sentence neural activity, techniques for stimulating neurons , what can be achieved with bidirectional BCI (I’m looking forward to building one 
), how to create synthetic neural data (next, I will implement it), some biology, and how to verify the solutions of the Schrödinger equation
P/S: hic, i have 9 images, but can only post one !!! need to wait few days…
the last two days i learned: fixed some bugs in the decoder model for neural activity and dded some improvements to the generate protein model, some biology and filled some chemistry gaps in material science