Some Media Accounts I Keep Track Of

Good Medium Conveys Readable Knowledge

I apprecaite those medium accounts which use the most recent web techlogies(d3.js, disqus,etc) to make their content vivid and interactive. I usually keep track of the updates of these medium accounts.

• https://awni.github.io/ Awni is a Stanford PhD. Although it has only 3 blogs, but they can be good templates if you want to good academic blogs.
• http://otoro.net/ Hardmaru and David Ha(They are the same person, but at first I am confused with the two names). Twitter https://twitter.com/hardmaru Google Tokyo guy, very smart and productive. I especially love his blogs about reinforcement learning(evolution strategies etc)
• http://amid.fish/ Another goodfellow in writing blogs and RL. His blog is necessary to read if you want to dive into it! And his blog about distributed tensorflow helped me a lot when I played with tensorflow.
• https://distill.pub/ A high quality medium oriented at broadcasting machine learnig explanity only. You can try to win their prize.
• http://bair.berkeley.edu/blog/ Berkeley AI lab focuses on reinforcemnt learning and intelligent robots. The PhDs of Bair also have very good blogs. Maybe they are required to do so by Bair. I will update their blog links later. And PRs are also welcome! If you want to track the most recent research about DRL. Don’t miss it!
• https://blog.openai.com/ OpenAI is awesome in DRL. I especially love their github codebase. Lots of insightful and modular code about RL research is worthywhile for you to explore for at least one month. Deepmind is also good, but when you talk about code publicity, you’d better walk away. I love google and their products, but Deepmind cannot attract me. Serioully speaking, I think everyone in the circle welcomes publicity and openness to push AI forward. But you can only see Deepmind’s new fancy results in their paper. You can understand they try to state their experiment details as possible as they can. But why not just release the code like OpenAI?
• https://www.alexirpan.com Alex works in GoogleX on robotics and he has some great posts on thoughts about RL(https://www.alexirpan.com/page2/) and the most recent one which summaries his journey of ICLR and ICRA(https://www.alexirpan.com), it’s awesome!
• https://adeshpande3.github.io/ Adit Deshpande is a CS Undergrad at UCLA (‘19). His posts covers a broad topic from CNN to RL. this is a good post for understanding neural network architecture.
• http://www.gitxiv.com/page/competitions GitXiv is a space to share collaborative open computer science projects. Countless Github and arXiv links are floating around the web. Its hard to keep track of these gems. GitXiv attempts to solve this problem by offering a collaboratively curated feed of projects. Each project is conveniently presented as arXiv + Github + Links + Discussion. Members can submit their findings and let the community rank and discuss it. A regular newsletter makes it easy to stay up-to-date on recent advancements. It´s free and open. There are many repos for interesting papers. In my spare time, I’d like to contribute to the GitXiv.
• https://paperswithcode.com/ The site that the paper and the code are gathered together in a set. I subscribe and send a weekly digest-ish. Papers with Code: The latest in machine learning: https://paperswithcode.com/
• https://ben-eysenbach.github.io/ Ben Eysenbach is a Resident at Google Brain who (attempts to) teach robots. Before joining Brain, he studied math and computer science at MIT. I will start my PhD in CMU’s Machine Learning Department in Fall 2018.
• http://www.stefan-pochmann.info/spots/tutorials/ Stefan Pochmann is a very powerful player in competitive programming, also in leetcode, yes, the interviewing question website, I found Pochmann through his beautiful solutions for these algo problems.
• http://www.argmin.net/arg min blog: a blog of minimum value** Musings on systems, information, learning, and optimization by Ben Recht. With intermittent ramblings about music. Ben is a professor in Berkeley on DRL and control. Many blogs on argmin has deep sights on reinforcement learning. It’s worthy of a read.
• https://l1aoxingyu.github.io/Liao is a PKU student and has a fantastic blog about machine learning, mostly using Pytorch.
• https://towardsdatascience.com/@pietz After one semester’s study of computer vision, I gained some foundamental knowledge of computer vision. Paul has written some good posts about computer vision architectures including mobile-Net.
• https://tryolabs.com/blog/2018/01/18/faster-r-cnn-down-the-rabbit-hole-of-modern-object-detection/ Tryolabs also has some great posts about computer vision. Check it out!
• https://lilianweng.github.io/lil-log/ Lili Weng works at Robotics of OpenAI, she has great posts, both in style and contents. I always want to become as proficient as her in writing tech blogs, but I know first I have to become very professional in the domain. So cheer up!
• https://blog.evjang.com/ Eric Jang works at Google Brain and also writes about the most recent advancement in the ML community. He is good at writing complex math knowledge in an understandable way.
• https://kasparmartens.rbind.io/ KASPAR MÄRTENS is a PhD student at Oxford, this blog is mostly about statistical machine learning and Bayesian inference. It’s a very interactiva and vivid site with the help of Rbind. I am considering borrowing the suppor of Rbind to make my blog more interactive.
• https://blog.csdn.net/xiaoxiaowenqiang The github account is Ewenwan, there are tons of tech stuff(Vision, SLAM, C++ programming) in the github repo and the csdn blog in Chinese.
• https://colindcarroll.com Carroll is a maintainer of PyMC3, many blogs about bayesina ML are on this site.
• http://www.bnikolic.co.uk/blog Many interesting blogs about high-performance computing and C++ programming.
• https://www.acodersjourney.com/ A site of C++ programming and software engineering.