Blog Directory
Top level » Machine learning » Tutorials Expectation-Maximization (EM)   PyTorch tutorials       A Beginner’s Guide to Restricted Boltzmann Machines   An overview of convolutional neural network architectures (CNNs)   An overview of gradient descent optimization algorithms  Sebastian Ruder Awesome deep vision   - curated list of deep learning resources for computer vision. Awesome TensorFlow   - a curated list of TensorFlow projects Deep learning reading list   Deep Learning Tutorials — Deep Learning v0.1 documentation   GIBBS SAMPLING FOR THE UNINITIATED  Philip Resnik, Eric Hardisty MLDemos  Basilio Noris - Visualization of machine learning. Most Cited Deep Learning Papers  Terry Taewoong Um Neural Machine Translation (seq2seq) Tutorial   Notebooks and code for the book "Introduction to Machine Learning with Python"   Probabilistic Programming for Anomaly Detection   scikit-learn tutorials from Kaggle   State of the art Stochastic Gradient Descent methods: an excellent overview  Yaroslav Bulatov Top 10 algorithms in data mining  Xindong Wu, Vipin Kumar, J Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J McLachlan, Angus Ng, Bing Liu, S Yu Philip, Zhi-Hua Zhou, Michael Steinbach, David J Hand, Dan Steinberg Training Sequence Models with Attention  Awni Hannun - practical tips to train seq-to-seq models. Visualization of neural network learning   What it takes to build great machine learning products  Aria Haghighi