I find myself revisiting highly interestign Twitter threads. Here is a list of the most interesting threads sorted by topics …
Machine Learning
Critical ML topics for the coming 3-4 years by @soniajoseph_. The replies to the thread are insightful.
machine learning twitter--
— Sonia Joseph (@soniajoseph_) October 20, 2022
ML is moving fast. Which research ideas / PhD topics will remain critical 3-4 years from now?
@ericmander on “Foundation models are the new public cloud and AI is the new SaaS”
machine learning twitter--
— Sonia Joseph (@soniajoseph_) October 20, 2022
ML is moving fast. Which research ideas / PhD topics will remain critical 3-4 years from now?
@jobergum on bad ML experiences caused by ML batch systems
Many bad online experiences are caused by predictions done by batch-oriented ML systems that do not consider the real-time context.
— Jo Kristian Bergum (@jobergum) October 1, 2022
Great thread on light weight Python setups to deploy ML models by @simonw This replies to this tweet offer a number of interesting options.
What's the lightest Python dependency (in terms of complexity/amount of code/ideally no compiled dependencies) that would let me add a tiny ML model to a Python application? For inference against a bundled model, not for training the model itself
— Simon Willison (@simonw) October 2, 2022
A thread on way embedding are a pain in the *** by @mlopscommunity Great thread about embedding and the hidden complexity.
What's the lightest Python dependency (in terms of complexity/amount of code/ideally no compiled dependencies) that would let me add a tiny ML model to a Python application? For inference against a bundled model, not for training the model itself
— Simon Willison (@simonw) October 2, 2022
A thread about real time ML by @mlopscommunity
Why are building real-time data pipelines in machine learning so challenging?
— MLOps Community (@mlopscommunity) August 26, 2022
Let's talk about it in this 🧵
MLOps
Great thread by @GoAbiAryan on papers around ML system designs.
This has been such an excellent year for software system design in ML. So, I compiled a list of some of my favorite papers 📜in MLOps.
— Abi Aryan (@GoAbiAryan) October 14, 2022
Here are some of my favorite ones till date⤵️
Startups
Advice on good pitch decks by @wallstreetpaper
At @HarlemCapital we see 4k+ pitch decks a year
— Brandon (wallstreetpaper.eth) (@wallstreetpaper) October 20, 2022
Here are the the 10 slides you should have in your pitch deck
A THREAD 🧵
