Data Science at Home
Episodes

Friday Oct 30, 2020
What is contrastive learning and why it is so powerful? (Ep. 124)
Friday Oct 30, 2020
Friday Oct 30, 2020
Come join me in our Discord channel speaking about all things data science.
Follow me on Twitch during my live coding sessions usually in Rust and Python
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References
A Simple Framework for Contrastive Learning of Visual Representations

Friday Oct 23, 2020
Neural search (Ep. 123)
Friday Oct 23, 2020
Friday Oct 23, 2020
Come join me in our Discord channel speaking about all things data science.
Follow me on Twitch during my live coding sessions usually in Rust and Python
This episode is supported by Monday.com
The Monday Apps Challenge is bringing developers around the world together to compete in order to build apps that can improve the way teams work together on monday.com.

Sunday Oct 18, 2020
Let's talk about federated learning (Ep. 122)
Sunday Oct 18, 2020
Sunday Oct 18, 2020
Let's talk about federated learning. Why is it important? Why large organizations are not ready yet?
Come join me in our Discord channel speaking about all things data science.
Follow me on Twitch during my live coding sessions usually in Rust and Python
This episode is supported by Monday.com
The Monday Apps Challenge is bringing developers around the world together to compete in order to build apps that can improve the way teams work together on monday.com.

Sunday Oct 11, 2020
How to test machine learning in production (Ep. 121)
Sunday Oct 11, 2020
Sunday Oct 11, 2020
Come join me in our Discord channel speaking about all things data science.
Follow me on Twitch during my live coding sessions usually in Rust and Python
This episode is supported by Monday.com
Monday.com bring teams together so you can plan, manage and track everything your team is working on in one centralized place
The monday Apps Challenge is bringing developers around the world together to compete in order to build apps that can improve the way teams work together on monday.com.

Friday Sep 04, 2020
Testing in machine learning: checking deeplearning models (Ep. 118)
Friday Sep 04, 2020
Friday Sep 04, 2020
In this episode I speak with Adam Leon Smith, CTO at DragonFly and expert in testing strategies for software and machine learning.We cover testing with deep learning (neuron coverage, threshold coverage, sign change coverage, layer coverage, etc.), combinatorial testing and their practical aspects.
On September 15th there will be a live@Manning Rust conference. In one Rust-full day you will attend many talks about what's special about rust, building high performance web services or video game, about web assembly and much more.If you want to meet the tribe, tune in september 15th to the live@manning rust conference.

Monday Aug 03, 2020
Test-First machine learning (Ep. 115)
Monday Aug 03, 2020
Monday Aug 03, 2020
In this episode I speak about a testing methodology for machine learning models that are supposed to be integrated in production environments.
Don't forget to come chat with us in our Discord channel
Enjoy the show!
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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.

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).
If you have comments about this episode or just want to chat, come join us on the official Discord channel.
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.
![[RB] It’s cold outside. Let’s speak about AI winter (Ep. 111)](https://pbcdn1.podbean.com/imglogo/image-logo/1799802/dsh-cover-2_300x300.jpg)
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.
Join us to our Discord channel to discuss your favorite episode and propose new ones.
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Monday Jun 15, 2020
Monday Jun 15, 2020
In this episode I have a chat with Sandeep Pandya, CEO at Everguard.ai a company that uses sensor fusion, computer vision and more to provide safer working environments to workers in heavy industry.Sandeep is a senior executive who can hide the complexity of the topic with great talent.
This episode is supported by Pryml.io Pryml is an enterprise-scale platform to synthesise data and deploy applications built on that data back to a production environment.Test ideas. Launch new products. Fast. Secure.

Monday Jun 01, 2020
Compressing deep learning models: rewinding (Ep.105)
Monday Jun 01, 2020
Monday Jun 01, 2020
As a continuation of the previous episode in this one I cover the topic about compressing deep learning models and explain another simple yet fantastic approach that can lead to much smaller models that still perform as good as the original one.
Don't forget to join our Slack channel and discuss previous episodes or propose new ones.
This episode is supported by Pryml.io Pryml is an enterprise-scale platform to synthesise data and deploy applications built on that data back to a production environment.
References
Comparing Rewinding and Fine-tuning in Neural Network Pruninghttps://arxiv.org/abs/2003.02389