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- Extreme learning machine - Wikipedia
en.wikipedia.org/wiki/Extreme_learning_machine

From 2001-2010, ELM research mainly focused on the unified learning framework for "generalized" single-hidden layer feedforward neural networks (SLFNs), including but not limited to sigmoid networks, RBF networks, threshold networks,[5] trigonometric networ.. - Machine Learning on Encrypted data without Decrypting it - Julia ComputingNov 2019 - If you’re not familiar with machine learning, or the Flux.jl machine learning library, I’d recommend a quick detour to the Flux.jl documentation or our free Introduction to Machine Learning course on JuliaAcademy, since we’ll only be discussing the changes ..
- Better machine learning | MIT News | Massachusetts Institute of Technology
news.mit.edu/2015/better-machine-learning-kalyan-veeramachaneni-0224

Data scientists go to all these boot camps in Silicon Valley to learn open source big data software like Hadoop, and they come back, and say ‘Great, but we’re still stuck with the problem of getting the raw data to a place where we can use all these tools,’.. - Machine Learning for Systems and Systems for Machine Learning
- Machine Learning 101. A brief introduction to machinea| | by Peter Roelants | Onfido Tech | Medium
medium.com/onfido-tech/machine-learning-101-be2e0a86c96a

The optimisation algorithm tries to find the best combination of parameters so that given the example x the model’s output y is as close to the expected output as possible. If we now want to create a model that best approximates target t for given input x f.. - Machine learning works spectacularly well, but mathematicians aren't sure why
quantamagazine.org/big-datas-mathematical-mysteries-20151203

I have always loved this point of view; it explains how applied mathematicians will always need to make use of the new concepts and structures that are constantly being developed in more foundational mathematics. As in other areas of machine learning, the h.. - Machine Learning for Developers by Mike de Waard
xyclade.github.io/MachineLearning

Most developers these days have heard of machine learning, but when trying to find an 'easy' way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learning and terms as regression, unsupervised.. - Machine Learning for Dummies
- Machine Learning for Everyone :: In simple words. With real-world examples. Yes, again :: vas3k.com
vas3k.com/blog/machine_learning/?ref=hn

The most exciting thing is that the machine copes with this task much better than a real person does when carefully analyzing all the dependencies in their mind. Recurrent networks gave us useful things like neural machine translation (here is my post about.. - 6.867 Machine Learning
ai.mit.edu/courses/6.867-f04/lectures.html

Mon 9/20||Lecture 4: statistical regression, uncertainty, active learning| Wed 9/29||Lecture 7: support vector machines, kernels||Notes on Lagrange multipliers (postscript)| Mon 10/25||Lecture 12: VC-bounds, structural risk minimization, compression and mod..