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AI/ML for Biology & Healthcare: A Learning Path

iamtk.co · published undated

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https://codeforces.com/
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http://learnpytorch.io/
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https://pandas.pydata.org/docs/getting_started/intro_tutorials/
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https://numpy.org/doc/stable/user/absolute_beginners.html
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https://www.labri.fr/perso/nrougier/from-python-to-numpy
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https://www.kaggle.com/code/utsav15/100-numpy-exercises
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https://www.codecademy.com/learn/eda-exploratory-data-analysis-python
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https://www.datacamp.com/courses/exploratory-data-analysis-in-python
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https://www.kaggle.com/learn/feature-engineering
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https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/
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https://www.coursera.org/learn/machine-learning
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https://www.coursera.org/learn/unsupervised-learning-recommenders-reinforcement-learning
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https://udlbook.github.io/udlbook/
udlbook.github.io
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A Gentle Introduction to Graph Neural Networks Read at the source ↗
distill.pub
https://learn.deeplearning.ai/courses/diffusion-models
learn.deeplearning.ai
https://www.youtube.com/playlist?list=PLqYmG7hTraZBKeNJ-JE_eyJHZ7XgBoAyb
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Causal inference resources Read at the source ↗
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http://rivaslab.org/teaching/MCB128_AIMB/downloads/BeplerBerger21.pdf
rivaslab.org
http://rivaslab.org/teaching/MCB128_AIMB/downloads/Ji21.pdf
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http://rivaslab.org/teaching/MCB128_AIMB/downloads/Nguyen24.pdf
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https://www.nature.com/articles/s41586-021-03819-2
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https://github.com/google-deepmind/alphafold
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https://github.com/google-deepmind/alphafold3
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https://www.biorxiv.org/lookup/doi/10.1101/2024.11.19.624167
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https://github.com/jwohlwend/boltz?tab=readme-ov-file
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https://www.biorxiv.org/content/10.1101/2024.10.10.615955v2
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https://github.com/chaidiscovery/chai-lab
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https://www.biorxiv.org/content/10.1101/2025.07.05.663018v1.full.pdf
biorxiv.org
https://arxiv.org/abs/2507.11839
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https://github.com/bytedance/Protenix
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https://www.pnas.org/doi/full/10.1073/pnas.2016239118
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https://github.com/facebookresearch/esm
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https://www.biorxiv.org/content/10.1101/2022.06.03.494563v1
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https://github.com/dauparas/ProteinMPNN
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https://www.biorxiv.org/content/10.1101/2023.09.11.556673v1
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https://github.com/microsoft/evodiff
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https://www.nature.com/articles/s41586-023-06728-8
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https://github.com/generatebio/chroma
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https://www.nature.com/articles/s41586-023-06415-8
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https://github.com/RosettaCommons/RFdiffusion
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https://github.com/baker-laboratory/rf_diffusion_all_atom
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https://github.com/RosettaCommons/RFantibody
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https://pmc.ncbi.nlm.nih.gov/articles/PMC7442218/pdf/nihms-1617552.pdf
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https://www.sciencedirect.com/science/article/abs/pii/S0933365725002003
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https://www.justinmath.com/how-to-get-from-high-school-math-to-cutting-edge-ml-ai
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https://www.khanacademy.org/math/linear-algebra
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https://www.khanacademy.org/math/multivariable-calculus
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https://www.khanacademy.org/math/statistics-probability
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https://www.mathacademy.com/courses/mathematics-for-machine-learning
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https://pabloinsente.github.io/intro-linear-algebra
pabloinsente.github.io
Building A Neural Network from Scratch with Mathematics and Python Read at the source ↗
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https://www.kaggle.com/code/gpreda/electronic-health-records-ehrs-data-exploration/notebook
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https://github.com/imteekay/machine-learning-research/blob/master/papers/sybil-a-validated-deep-learning-model-to-predict-future-lung-cancer-risk-from-a-single-low-dose/index.md
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https://www.ncbi.nlm.nih.gov/books/NBK21054/
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https://www.goodreads.com/book/show/345300.Molecular_Cell_Biology
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Just know stuff. (Or, how to achieve success in a machine learning PhD.) Read at the source ↗
kidger.site
https://www.youtube.com/watch?v=_xIwjmCH6D4
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https://www.youtube.com/watch?v=wOTFGRSUQ6Q
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https://www.khanacademy.org/math
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https://github.com/hussius/deeplearning-biology
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https://github.com/AstraZeneca/biology-for-ai
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https://www.tamarind.bio/blog/a-comprehensive-introduction-to-ai-for-proteins
tamarind.bio
https://bioinformatics.gatech.edu/sites/default/files/CX.4803.MLB_Syllabus.S24.pdf
bioinformatics.gatech.edu
Just know stuff, proteinML edition Read at the source ↗
kidger.site
https://www.youtube.com/playlist?list=PLypiXJdtIca4gtioEPLIExlAKvu64z7rc
youtube.com
http://rivaslab.org/teaching/MCB128_AIMB/
rivaslab.org
http://mcb111.org/
mcb111.org
https://www.coursera.org/specializations/deep-learning-healthcare
coursera.org
https://www.coursera.org/specializations/ai-for-medicine
coursera.org
https://teekay.substack.com
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https://twitter.com/wordsofteekay
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https://github.com/imteekay
github.com