Continuous Learning in Machine Learning
Rapidly evolving machine learning requires swift adaptation. Here I'll compile a list of intriguing, up-to-date courses and complete them as time permits.
- Group Equivariant Deep Learning This course go into details about Group Equivariant Deep Learning, featuring group convolutions, equivariant graph networks, and additional resources from Amsterdam ML Lab.
- Deep Learning Foundations to Stable Diffusion This course gives a in-depth exploration of the Stable Diffusion algorithm, which is a cutting-edge technique in the field of deep learning.
- Data Science Ethics This course explore the ethical and privacy implications of big data, focusing on fairness, accountability, transparency, and responsible data management.
Academic Success Resources: Tenure, Proposals, and Job Hunting
Here I'm maintaining a centralized list of resources related to achieving tenure, securing funding proposals, and academic job hunting.
- CS Professor Handbook This book offers insights and advice on navigating academia and achieving tenure.
- You and Your Research by Richard This article discusses the steps towards achieving greatness in research.
- Student Mentoring Guide This article list resources to have clear communication and shared expectations for a successful graduate student-advisor relationship.
- Funded Proposals and Tenure Resources These are openly available funded proposals and tenure materials to learn from them.
- NSF Career Award This article shares two NSF CAREER proposals, with the first being rejected and the second being successful.
- Open Access for All This article addresses equity in academia by posting their funded proposals online for public access.
- Academic Grant Funding This article talks about department overhead, summer salary, graduate students, travel, and other expenses such as equipment and user studies.
- Academic job hunting Tips These document offers tips for academic job hunting, covering phone interviews and on-site interviews.
Technical Writing and AI Conference
This collection of resources provides strategies for enhancing technical writing skills, reviewing other papers and successfully participating in AI/ML conferences.
- Tips for Writing Effective Technical Papers This article provides a comprehensive guide to writing technical papers.
- Crafting a High-Quality ML Paper This article provides all the essentials for writing a top-notch ML paper.
- Templates for Posters This website provides visually captivating posters template and other visualization stuff.
- How to be a good reviewer ? This presentation focuses on understanding the nature of the review process in the context of AI and machine learning conferences.
- Art of Writing Effective Rebuttals This article provides a comprehensive guide on how to write effective rebuttals in AI conferences, and include tips for clarity, directness, and persuasiveness.
- AI/ML Conference Deadlines
|ML/AI Conferences||Conference Dates||Conference Deadline|
|AAAI||Feb 07-14||Aug 15|
|WSDM||Mar 01-03||Aug 12|
|SDM||Apr 27-29||Oct 7|
|WWW||May 01-04||Oct 13|
|ICLR||May 01-05||Sep 28|
|PAKDD||May 25-28||Dec 7|
|ICASSP||Jun 04-10||Oct 26|
|SIGIR||Jul 23-27||Jan 31|
|ICML||Jul 23-29||Jan 26|
|KDD||Aug 06-10||Feb 02|
|IJCAI||Aug 19-25||Jan 18|
|CIKM||Oct 21-25||Jun 02|
|ICDM||Dec 01-04||Jul 01|
|NeurIPS||Dec 10-16||May 17|