Cutting Edge Deep Learning
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πŸ“• Deep learning
πŸ“— Reinforcement learning
πŸ“˜ Machine learning
πŸ“™ Papers - tools - tutorials

πŸ”— Other Social Media Handles:
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Why walk when you can flop?
In one example, a simulated robot was supposed to evolve to travel as quickly as possible. But rather than evolve legs, it simply assembled itself into a tall tower, then fell over. Some of these robots even learned to turn their falling motion into a somersault, adding extra distance.

Blog by Janelle Shane: https://lnkd.in/dQnCVa9

Original paper: https://lnkd.in/dt63hJR

#algorithm #artificialintelligence #machinelearning #reinforcementlearning #technology

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@machinelearning_tuts
πŸ”ΉHow Algorithms Can Predict Our Intentions Faster Than We Can

Artificial Intelligence (AI) and Natural Language Processing (NLP) can gather data from anywhere online where we leave a mark. This includes our social media posts, our email, and even any small comments we leave on blog posts. Every trace we leave online allows NLP to track and predict our future decisions.
This article highlight how NLP can impact our day-to-day lives with the use of case studies.

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https://www.entrepreneur.com/article/328776

πŸ“ŒVia: @cedeeplearning

#NLP
#AI
#machinelearning
#deeplearning
#algorithm
πŸ”ΉAlgorithms, Libraries, Toolkits and Platforms…

There are a multitude of technologies and frameworks on the market today that enable data scientists and machine learning engineers to build, deploy and maintain machine learning systems, pipelines and workflows. Just like any economic matter, supply and demand drives the improvement and progress of the product. As the use of machine learning in business increases, so does the number of frameworks and software that facilitate full-fledged machine learning workflows.
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πŸ“ŒVia: @cedeeplearning
πŸ“ŒSocial media: https://linktr.ee/cedeeplearning

link: https://www.rocketsource.co/blog/machine-learning-models/

#machinelearning
#algorithm
#library
#platform
#technology
⭕️ A foolproof way to shrink deep learning models

​Researchers unveil a pruning algorithm to make artificial intelligence applications run faster.

πŸ–‹By Kim Martineau

As more artificial intelligence applications move to smartphones, deep learning models are getting smaller to allow apps to run faster and save battery power. Now, MIT researchers have a new and better way to compress models.
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πŸ“ŒVia: @cedeeplearning

http://news.mit.edu/2020/foolproof-way-shrink-deep-learning-models-0430

#deeplearning #AI #model
#MIT #machinelearning
#datascience #neuralnetworks
#algorithm #research