Archive for the 'Artificial Intelligence' Category

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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

Our Sponsors

  • Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.

 

References

Dataset distillation (official paper)

GitHub repo

 

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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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  • Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.

References

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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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  • Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.

 

References

A Simple Framework for Contrastive Learning of Visual Representations

 

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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.

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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.

 

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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.

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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.

 

 

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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.

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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.

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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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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.

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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 Pruning
https://arxiv.org/abs/2003.02389

 

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Using large deep learning models on limited hardware or edge devices is definitely prohibitive. There are methods to compress large models by orders of magnitude and maintain similar accuracy during inference.

In this episode I explain one of the first methods: knowledge distillation

 Come join us on Slack

Reference

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In this episode I briefly explain the concept behind activation functions in deep learning. One of the most widely used activation function is the rectified linear unit (ReLU). 
While there are several flavors of ReLU in the literature, in this episode I speak about a very interesting approach that keeps computational complexity low while improving performance quite consistently.

This episode is supported by pryml.io. At pryml we let companies share confidential data. Visit our website.

Don't forget to join us on discord channel to propose new episode or discuss the previous ones. 

References

Dynamic ReLU https://arxiv.org/abs/2003.10027

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