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Hi there, you’re on the free list for our news digest TheSequence Scope. Every Sunday we pick the most relevant ML research papers, cool ML tech releases, and cover important investments in AI. Thank you for signing up! Follow us on Twitter.
— The other really cool thing that we’ve created is our Premium newsletter TheSequence EdgeWhy subscribe? To save yourself time and nerves, and to become much smarter about AL&ML. It’s brutally hard to follow what’s happening in the AI&ML world by yourself. It’s just TOO much. We explain the most relevant ML concept, link it to the important research paper and connect with practical implementation. We also cover What’s New in AI, providing you with deep dives into significant research papers and tech frameworks that are worth it. Our subscribers tell us that TheSequence Edge often gives them new ideas for the projects they are working on. The content is unique, it’s trusted by the main AI labs and universities of the world. Usually, it is $5/month or $50/year. Subscribe today with 10% OFF, this is only for newcomers. You will be in good company: A few topics we’ve already covered in TheSequence Edge:Automated Machine LearningAutoML and ideas for automating the creation of machine learning models are becoming a super hot topic. We covered that topic in the following editions of The Sequence Edge: Edge#4: Neural Architecture Search (read it without subscription)
Edge#2: AutoML (read it without subscription)
Edge#11: Meta-Learning (read it without subscription)
Generative ModelsHow to generate synthetic data that looks just like the real thing? How about networks competing with each other to improve learning. Check out the following issues of The Sequence Edge which cover topics related to generative models.
Edge#8: Generative Adversarial Neural Networks
Feature EngineeringConsidered by many one of the most important topics in real-world machine learning solutions, feature selection and engineering is a never-ending area of research and innovation. You can learn more about it in the following issues. Edge#10: Feature Extraction vs. Feature Selection
Edge#25: Representation Learning
Practical Machine LearningTheSequence Edge regularly discusses topics related to best practices and techniques to run machine learning models in production at scale. Here are some of our favorites.
Emerging Learning MethodsModern machine learning goes beyond supervised and unsupervised learning. Check out some of the new learning paradigms that are likely to become more relevant in the near future. Edge#14: Semi-Supervised Learning
Edge#26: Self-Supervised Learning
No-nonsense, no-hype repository of information, TheSequence will help you gradually and easily learn different parts and aspects of the ML Universe. |
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👓 Edge#135: Self-Supervised Learning for Computer Vision
Friday, October 29, 2021
The conclusion of our self-supervised learning series
🎙 Olga Megorskaya/Toloka: Practical Lessons About Data Labeling
Friday, October 29, 2021
and balance between fully automated, crowdsourced or hybrid approaches to data labeling
🔵⚪️Edge#136: Kili Technology and Its Automated Data-Centric Training Platform
Friday, October 29, 2021
Let's dive in
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