Artificial Intelligence

2021-08-15 04:48:21 Open / Comment

2021-08-11 19:37:39 OpenAI Codex

AI system that translates natural language to code.

OpenAI have created an improved version of OpenAI Codex, there AI system that translates natural language to code, and they are releasing it through there API in private beta starting today.

Codex is the model that powers GitHub Copilot, which we built and launched in partnership with GitHub a month ago. Proficient in more than a dozen programming languages, Codex can now interpret simple commands in natural language and execute them on the user’s behalf—making it possible to build a natural language interface to existing applications. We are now inviting businesses and developers to build on top of OpenAI Codex through our API. https://openai.com/blog/openai-codex/


This is Completely a Game changer

You can even do Machine learning & Data science with it by just writing what would you like to do with a data set and it will produce live Python code with the solution.

Edit: YouTube Video Link

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2021-08-11 17:30:03 Notable new paper with great insights on the importance of collaboration to improve and accelerate progress in machine learning.

"Collaboration is the most powerful way to improve the state-of-the-art in Machine Learning."

Cool paper using paperswithcode.com data looking at community dynamics for ML benchmarks.

Check it out below:
https://www.nature.com/articles/s42256-021-00339-6.epdf Open / Comment

2021-08-08 18:36:19 An Introduction for Statistical Learning
I call this book as Bible for applied statistics and machine learning, and I use it as my first go-to resource for any regression problem.

The book covers following topics:
Sparse methods for classification and regression
Decision trees and Boosting
Support vector machines
Clustering

Recently 2nd edition is released and topics added to the 2nd edition are:
Deep learning
Survival analysis
Multiple testing
Naive Bayes, linear Models
Bayesian additive regress trees
Matrix completion

This books hard copy is available on Amazon

And PDF version is available for FREE here. Open / Comment

2021-08-06 19:51:57 If you’re a Data Scientist trying to level up, go read case studies.

Data Science is less about knowing the nuances of a particular library/tool, but more about its application to solving business problems.

Case studies from companies help you understand how projects operate, from start to end, and the practical ways Data Science is applied in the real world.

Case studies crucially show you the underlying business needs which motivate the technical solution — something which sadly gets missed in most DS classes

Here’s a fun case study from Netflix on how they use ML to decide what new shows & movies to make.

Here’s a case study from Uber on how they use graph theory + ML to find users making fraudulent trips.

Here’s a case study from Airbnb on how they track marketing data at scale.(credits: Nick Singh)

What's your favorite company blog or source for Data Science case studies?

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2021-08-05 19:26:10 Open / Comment