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- Type4Py: Machine Learning-Based Type Auto-Completion for Python
- A friendly introduction to machine learning compilers and optimizers
- The code from the Machine Learning Bookcamp book and a free course based on the book (Jupyter Notebook)
- CrypTen: Secure Multi-Party Computation Meets Machine Learning
- Machine Learning
cs.ox.ac.uk/people/nando.defreitas/machinelearningPlease click on Timetables on the right hand side of this page for time and location of the practicals. Practicals will use Torch, a powerful programming framework for deep learning that is very popular at Google and Facebook research. Please click on Timet..
- Machine Learning for Developers by Mike de Waard
xyclade.github.io/MachineLearningMost 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..
- xkcd: Machine Learning
- Machine Learning Trends from NIPS 2014 | Microsoft Docs
docs.microsoft.com/en-us/archive/blogs/machinelearning/machine-learning-trends-from-nips-2014Training in machine learning is a form of parameter optimization: an ML model can be viewed as having a set of knobs that are adjusted to make the model perform well on a training set. Yurii Nesterov, a famous optimization expert, gave an interesting invite..
- A Machine Learning Guide for Average Humans - Moz
moz.com/blog/learning-machine-learningIt's about regular Joes and Joannas with an interest in machine learning, and who want to spend their learning time efficiently. Read content focused on teaching the breadth of machine learning -- building an intuition for what the algorithms are trying to ..
- Machine Learning for Beginners: An Introduction to Neural Networks - victorzhou.com
victorzhou.com/blog/intro-to-neural-networksWe’ll use NumPy, a popular and powerful computing library for Python, to help us do math: Learned about loss functions and the mean squared error (MSE) loss. Experiment with bigger / better neural networks using proper machine learning libraries like Tensor..