Stanford computer science professor just revealed how to master Markov Decision Processes.
83-minutes. free. By Stanford.
here's what they cover:
• search problems vs. stochastic environments
• policy evaluation & q-value recurrence math
• value iteration loop engineering
• convergence limits under a cyclic graphs
Bookmark & watch today. Then read the article below.
2024 is the year for Causal AI! 💥
Infosys found that only 6% of EU companies are producing business value with their GenAI use cases. GenAI still has a lot to prove.
Adi Andrei, former Senior Data Scientist at NASA, said, “Boardrooms need proof that [GenAI] investments will increase the bottom line.”
GenAI and traditional AI/ML methods aren’t measured against business objectives, and so efforts by Data Science teams often can’t go beyond the experimental phase.
2023 was a great year for Causal AI; bring on 2024!
You can read more here: https://t.co/1Fjt92T8P5
Find out about the causal revolution here: https://t.co/tY8OZj6oPO
#causalai #causality #ml
“Building a Deep Neural Net In Google Sheets” by @bwest87 https://t.co/wA0UOOGI7f
Yes this awesome teaching/learning project really is a working convolutional net in a spreadsheet!
Make most of 2018 now! Here's your learning path to learn #DataScience & pursue career as Data Scientist in most structured way. (Author: Kunal Jain) https://t.co/YwhVpDdCM1 #bigdata
Rankings are everywhere. They are sometimes useful and, at other times, contradicting. In such a case, we need to come up with a #consensusranking but... how do we evaluate ranking #Python#AI https://t.co/jgMBGdCuI1