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Sisällön tarjoaa Gianluca Truda and Jared Tumiel, Gianluca Truda, and Jared Tumiel. Gianluca Truda and Jared Tumiel, Gianluca Truda, and Jared Tumiel tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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025 | Self-Supervised Machine Learning: Introduction, Intuitions, and Use-Cases

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Manage episode 255440124 series 2633102
Sisällön tarjoaa Gianluca Truda and Jared Tumiel, Gianluca Truda, and Jared Tumiel. Gianluca Truda and Jared Tumiel, Gianluca Truda, and Jared Tumiel tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

On this episode of Bit of A Tangent, we discuss the emerging field of self-supervised machine learning. This is an immensely exciting area of active research in machine learning and AI - one which most people haven’t even heard about yet! We build up to the intuition for the topic by covering supervised and unsupervised learning; autoencoders and dimensionality reduction, and exploring how these techniques could be applied to Gianluca’s Quantified Self n=1 sleep quality dataset. We culminate in a detailed discussion of the state-of-the-art Contrastive Predictive Coding model, and how it allows us to learn about the structure of the world, without tonnes of labelled training data!

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Shownotes:

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Jared on Twitter: www.twitter.com/jnearestn

Gianluca on Twitter: www.twitter.com/QVagabond

Bit of a Tangent on Twitter (www.twitter.com/podtangent) and Instagram (instagram.com/podtangent/)

Summer school on Computational Neuroscience: http://imbizo.africa/

Control problem in AI: https://intelligence.org/stanford-talk/

Coordination problem: https://conceptually.org/concepts/coordination-problems

Deep learning overview: https://lilianweng.github.io/lil-log/2017/06/21/an-overview-of-deep-learning.html

t-SNE explained: https://mlexplained.com/2018/09/14/paper-dissected-visualizing-data-using-t-sne-explained/

Variational autoencoders explained: https://anotherdatum.com/vae.html

Self-supervised learning by fast.ai: https://www.fast.ai/2020/01/13/self_supervised/

CPC model papers on Arxiv: https://arxiv.org/pdf/1807.03748.pdf https://arxiv.org/pdf/1905.09272.pdf

Blog posts explaining CPC: https://lilianweng.github.io/lil-log/2019/11/10/self-supervised-learning.html

https://yann-leguilly.gitlab.io/post/2019-09-29-representation-learning-with-contrastive-predictive-coding/

https://mf1024.github.io/2019/05/27/contrastive-predictive-coding/

  continue reading

31 jaksoa

Artwork
iconJaa
 
Manage episode 255440124 series 2633102
Sisällön tarjoaa Gianluca Truda and Jared Tumiel, Gianluca Truda, and Jared Tumiel. Gianluca Truda and Jared Tumiel, Gianluca Truda, and Jared Tumiel tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

On this episode of Bit of A Tangent, we discuss the emerging field of self-supervised machine learning. This is an immensely exciting area of active research in machine learning and AI - one which most people haven’t even heard about yet! We build up to the intuition for the topic by covering supervised and unsupervised learning; autoencoders and dimensionality reduction, and exploring how these techniques could be applied to Gianluca’s Quantified Self n=1 sleep quality dataset. We culminate in a detailed discussion of the state-of-the-art Contrastive Predictive Coding model, and how it allows us to learn about the structure of the world, without tonnes of labelled training data!

--------

Shownotes:

--------

Jared on Twitter: www.twitter.com/jnearestn

Gianluca on Twitter: www.twitter.com/QVagabond

Bit of a Tangent on Twitter (www.twitter.com/podtangent) and Instagram (instagram.com/podtangent/)

Summer school on Computational Neuroscience: http://imbizo.africa/

Control problem in AI: https://intelligence.org/stanford-talk/

Coordination problem: https://conceptually.org/concepts/coordination-problems

Deep learning overview: https://lilianweng.github.io/lil-log/2017/06/21/an-overview-of-deep-learning.html

t-SNE explained: https://mlexplained.com/2018/09/14/paper-dissected-visualizing-data-using-t-sne-explained/

Variational autoencoders explained: https://anotherdatum.com/vae.html

Self-supervised learning by fast.ai: https://www.fast.ai/2020/01/13/self_supervised/

CPC model papers on Arxiv: https://arxiv.org/pdf/1807.03748.pdf https://arxiv.org/pdf/1905.09272.pdf

Blog posts explaining CPC: https://lilianweng.github.io/lil-log/2019/11/10/self-supervised-learning.html

https://yann-leguilly.gitlab.io/post/2019-09-29-representation-learning-with-contrastive-predictive-coding/

https://mf1024.github.io/2019/05/27/contrastive-predictive-coding/

  continue reading

31 jaksoa

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