{"id":28459403,"url":"https://github.com/kritikalcoder/ground_up_basics_trust_ml","last_synced_at":"2026-02-05T20:33:05.089Z","repository":{"id":69048987,"uuid":"600713299","full_name":"Kritikalcoder/ground_up_basics_trust_ml","owner":"Kritikalcoder","description":"A collection of useful educational resources to build a solid understanding of Trustworthy ML. 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While there are many wonderful resources out there, this collection focuses on the required basics. This list is in no way complete and I encourage others to contribute to it :) \n\n### **Topics**\n- Probability\n- Statistics\n- Calculus\n- Linear Algebra\n- Machine Learning\n- Deep Learning\n- Trustworthy Machine Learning\n- Privacy\n- Fairness\n- Interpretability \u0026 Explainability\n- Causality\n- Adversarial Attacks \u0026 Robustness\n- Other Topics\n\n### **Probability**\n- Stanford's course CS109: [Probability for Computer Scientists](https://web.stanford.edu/class/archive/cs/cs109/cs109.1214/)\n\n\n### **Statistics**\n\n### **Calculus**\n\n### **Linear Algebra**\n\n### **Machine Learning**\n- Book on [Mathematics for Machine Learning](https://mml-book.github.io/book/mml-book.pdf)\n- Coursera's [Machine Learning Specialization](https://in.coursera.org/specializations/machine-learning-introduction)\n- Andrew Zisserman's course on [Machine Learning](https://www.robots.ox.ac.uk/~az/lectures/ml/index.html)\n\n### **Deep Learning**\n- Coursera's [Deep Learning Specialization](https://www.coursera.org/specializations/deep-learning)\n- Ian Goodfellow's book on [Deep Learning](https://www.deeplearningbook.org/)\n\n### **Trustworthy Machine Learning**\nNote that a majority of the resources mentioned from this section onwards is re-shared from [trustworthyml.org](https://www.trustworthyml.org/resources) - a wonderful and thorough curation.\n- Nicolas Papernot's talk on [What does it mean for ML to be trustworthy?](https://www.youtube.com/watch?v=UpGgIqLhaqo)\n- Golnoosh Farnadi's course on [Trustworthy Machine Learning](https://gfarnadi.github.io/courses/TrustworthyMLF22/lectures.html)\n- [Begginer's list for research papers in Trustworthy ML](https://trustworthy-machine-learning.github.io/) by Reza Shokri and Nicolas Papernot \n\n### **Privacy**\n- Gautam Kamath's course: [Algorithms for Private Data Analysis](http://www.gautamkamath.com/CS860-fa2020.html)\n- Ted's blog series: [Why Differential Privacy is Awesome](https://desfontain.es/privacy/differential-privacy-awesomeness.html)\n- Facebook AI's Udacity course: [Secure and Private AI](https://www.udacity.com/course/secure-and-private-ai--ud185)\n- OpenMined's courses: [The Private AI Series](https://courses.openmined.org/courses)\n\n### **Fairness**\n\n### **Interpretability \u0026 Explainability**\n\n### **Causality**\n\n### **Adversarial Attacks \u0026 Robustness**\n\n### **Other Topics**\n- Ethics\n- Security\n- Accountability\n- Safety\n- Confidentiality\n- Unlearning/Forgetting\n- Decentralization/Federated Learning\n\n### **Other Related and Larger Collections**\n- [Awesome ML Fairness](https://github.com/brandeis-machine-learning/awesome-ml-fairness)\n- [Awesome Trustworthy Deep Learning](https://github.com/MinghuiChen43/awesome-trustworthy-deep-learning)\n\n### **References**\n- [Trustworthyml.org](https://www.trustworthyml.org/home): This website provides a wonderful introduction and set fo resources to various sub-fields in Trustworthy ML.\n\n### **Credits** \nOne step in the process of creating this collection was reaching out to fellow Trustworthy ML enthusiasts and practioners openly on twitter (https://twitter.com/kritipraks/status/1624062696319770624). I'm thankful to the following people's recommendations (found in replies to the tweet): @iPrabhavKaula @DoUseBrainCells @uhsnayvid @miguelguirao @rohithpudari @IMossavat @hrbigelow @mzahmad_92 @AbhayPuri98 @mean_numpy_user @iot_01edge @it_s_katherine @AmolSingbal :)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkritikalcoder%2Fground_up_basics_trust_ml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkritikalcoder%2Fground_up_basics_trust_ml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkritikalcoder%2Fground_up_basics_trust_ml/lists"}