Hi there,
I am Walter (tw, li), and it is great to be connected. It has been some weeks since our last edition, but here we are, ready to share some curated content from the last weeks.
If you enjoy this newsletter, feel free to forward it to your friends or colleagues, the more the merrier!
W.
In focus
One of the hottest topics in the last weeks has been Copilot. Copilot is an AI Pair Programming system by GitHub. Trained on millions of lines of code, it autocompletes big pieces of code based on context, comments and some seed code.
Please don’t use Copilot, by Engineer Man. Always interesting and to the point.
OpenAI Launches GitHub Copilot: AI Focused On Code Generation. Should We Be Worried Now?
And of course: OpenAI warns AI behind GitHub’s Copilot may be susceptible to bias.
More from de web
My Journey to Deep Learning. By Jeremy Howard. Video.
Enabling the 'imagination' of artificial intelligence. A team of researchers at USC is helping AI imagine the unseen, a technique that could also lead to fairer AI, new medicines and increased autonomous vehicle safety.
Facebook is ditching plans to make brain-reading headsets. The company's research into a consumer mind-reading device is over, for now. Some scientists said it was never possible anyway.
New map created by AI reveals hidden links between Milky Way and Andromeda galaxies. A new cosmic map revealed hidden structures connecting galaxies, which could help scientists model a future collision between the Milky Way and Andromeda, our galaxy's nearest neighbor. The map, made with machine learning, may also shed more light on dark matter's influence in the evolution of our universe.
This AI lets you generate new verses from your favorite rappers.
When curation becomes creation. The vanishing distinction between platforms and creators.
Learn something!
Gaussian Processes From scratch. This post explores some concepts behind Gaussian processes, such as stochastic processes and the kernel function.
data-curricula
Permanent work in progress. If you think there is something interesting that belongs to this list(s), let me know.
So far, in this repo:
Data curriculum - The Original. A collection of learning material covering analytics, DS, ML, etc. From medium to advanced. Mostly focused on Python, when a programming language is relevant. May also contain material from the other curricula in this section (see below).
Selected Libraries, Modules and Tools. A selection of things I find useful, interesting or curious. More hands-on material for somehow experienced users. Not really learning material. Again, mostly Python centric.
Probable Cause. Resources to learn Experiment Design, A/B testing, Bayes applications to Decision Science, Graphical Modelling, MCMC and probabilistic programming among other -related- topics.
Boost your Data Analysis and BI. Resources to learn how to process and extract value from data using data analysis and BI tools like Excel, PowerBI and others. Ideal for analysts and professionals that are already dealing with data -for example in Excel- and need to go to the next level. (Soon!)