Data Science at Home
Episodes
Sunday Jul 26, 2020
GPT-3 cannot code (and never will) (Ep. 114)
Sunday Jul 26, 2020
Sunday Jul 26, 2020
The hype around GPT-3 is alarming and gives and provides us with the awful picture of people misunderstanding artificial intelligence. In response to some comments that claim GPT-3 will take developers' jobs, in this episode I express some personal opinions about the state of AI in generating source code (and in particular GPT-3).
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This episode is supported by Amethix Technologies.
Amethix works to create and maximize the impact of the world’s leading corporations, startups, and nonprofits, so they can create a better future for everyone they serve. They are a consulting firm focused on data science, machine learning, and artificial intelligence.
Wednesday Jul 22, 2020
Make Stochastic Gradient Descent Fast Again (Ep. 113)
Wednesday Jul 22, 2020
Wednesday Jul 22, 2020
There is definitely room for improvement in the family of algorithms of stochastic gradient descent. In this episode I explain a relatively simple method that has shown to improve on the Adam optimizer. But, watch out! This approach does not generalize well.
Join our Discord channel and chat with us.
References
More descent, less gradient
Taylor Series
Sunday Jul 19, 2020
Sunday Jul 19, 2020
In this episode I speak about data transformation frameworks available for the data scientist who writes Python code. The usual suspect is clearly Pandas, as the most widely used library and de-facto standard. However when data volumes increase and distributed algorithms are in place (according to a map-reduce paradigm of computation), Pandas no longer performs as expected. Other frameworks play a role in such context.
In this episode I explain the frameworks that are the best equivalent to Pandas in bigdata contexts.
Don't forget to join our Discord channel and comment previous episodes or propose new ones.
This episode is supported by Amethix Technologies
Amethix works to create and maximize the impact of the world’s leading corporations, startups, and nonprofits, so they can create a better future for everyone they serve. Amethix is a consulting firm focused on data science, machine learning, and artificial intelligence.
References
Pandas a fast, powerful, flexible and easy to use open source data analysis and manipulation tool - https://pandas.pydata.org/
Modin - Scale your pandas workflows by changing one line of code - https://github.com/modin-project/modin
Dask advanced parallelism for analytics https://dask.org/
Ray is a fast and simple framework for building and running distributed applications https://github.com/ray-project/ray
RAPIDS - GPU data science https://rapids.ai/
Friday Jul 03, 2020
[RB] It’s cold outside. Let’s speak about AI winter (Ep. 111)
Friday Jul 03, 2020
Friday Jul 03, 2020
In this episode I speak with Filip Piekniewski about some of the most worth noting findings in AI and machine learning in 2019. As a matter of fact, the entire field of AI has been inflated by hype and claims that are hard to believe. A lot of the promises made a few years ago have revealed quite hard to achieve, if not impossible. Let's stay grounded and realistic on the potential of this amazing field of research, not to bring disillusion in the near future.
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