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The video is reposted for educational purposes and encourages involvement in the field of research.
Source: https://icml.cc/virtual/2020/tutorial/5751
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The video was published under the license of the Creative Commons Attribution license (reuse allowed). It is reposted for educational purposes and encourages involvement in the field of research.
Source: https://youtu.be/5ck1wObN65c
"The state of Machine Learning Operations in 2019
[EuroPython 2019 - Talk - 2019-07-11 - Singapore [PyData track]
[Basel, CH]
By Alejandro Saucedo
This talk will provide an overview of the key challenges and trends in the productization of machine learning systems, including concepts such as reproducibility, explainability and orchestration. The talk will also provide a high level overview of several key open source tools and frameworks available to tackle these issues, which have been identified putting together the Awesome Machine Learning Operations list (https://github.com/EthicalML/awesome-production-machine-learning).
The key concepts that will be covered are:
* Reproducibility
* Explainability
* Orchestration of models
The reproducibility piece will cover key motivations as well as practical requirements for model versioning, together with tools that allow data scientists to achieve version control of model+config+data to ensure full model lineage.
The explainability piece will contain a high level overview of why this has become an important topic in machine learning, including the high profile incidents that tech companies have experienced where undesired biases have slipped into data. This will also include a high level overview of some of the tools available.
Finally, the orchestration piece will cover some of the fundamental challenges with large scale serving of models, together with some of the key tools that are available to ensure this challenge can be tackled.
...
https://www.youtube.com/watch?v=XI7Z0Jp7Lfc
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The video is reposted for educational purposes and encourages involvement in the field of research.
Source: https://icml.cc/Conferences/2020/ScheduleMultitrack?event=5756
Many ML tasks share practical goals and theoretical foundations with signal processing (consider, e.g., spectral and kernel methods, differential equation systems, sequential sampling techniques, and control theory). Signal processing methods are an integral part of many sub-fields in ML, with links to, for example, Reinforcement learning, Hamiltonian Monte Carlo, Gaussian process (GP) models, Bayesian optimization, and neural ODEs/SDEs.
This tutorials aims to cover aspects in machine learning that link to both discrete-time and continuous-time signal processing methods. Special focus is put on introducing stochastic differential equations (SDEs), state space models, and recursive estimation (Bayesian filtering and smoothing) for Gaussian process models. The goals are to (i) teach basic principles of direct links between signal processing and machine learning, (ii) provide an intuitive hands-on understanding of what stochastic differential equations are all about, (iii) show how these methods have real benefits in speeding up learning, improving inference, and model building—with illustrative and practical application examples. This is to show how ML can leverage existing theory to improve and accelerate research, and to provide a unifying overview to the ICML community members working in the intersection of these methods.
...
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The video is reposted for educational purposes and encourages involvement in the field of research.
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Source: NeurIPS
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The video was published under the license of the Creative Commons Attribution license (reuse allowed). It is reposted for educational purposes and encourages involvement in the field of research.
Source: https://2020.dl-lab.eu/virtual-summer-school-on-deep-learning/
...
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The video was published under the license of the Creative Commons Attribution license (reuse allowed). It is reposted for educational purposes and encourages involvement in the field of research.
Source: https://www.facebook.com/1620822758218702/videos/1001102260293556
...
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The video is reposted for educational purposes and encourages involvement in the field of research.
Source: https://slideslive.com/38915806
Paper: https://rlgm.github.io/papers/54.pdf
...
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