Useful machine learning resources for anyone under the sun.
- Concepts:
- Software/Tutorials:
- CS231n Convolutional Neural Networks for Visual Recognition
- http://colah.github.io/posts/2014-07-Conv-Nets-Modular/
- http://stats.stackexchange.com/questions/116362/what-does-the-convolution-step-in-a-convolutional-neural-network-do
- Pros and Cons:
- http://colah.github.io/posts/2014-03-NN-Manifolds-Topology/
- Active Image Clustering: Seeking Constraints from Humans to Complement Algorithms
- Learning Concept Embeddings with Combined Human-Machine Expertise
- Human-Centered Interactive Clustering for Data Analysis
- The Human is the Loop: New Directions for Visual Analytics
- NEURAL NETWORK-BASED CLUSTERING USING PAIRWISE CONSTRAINTS
- Visualizing MNIST: An Exploration of Dimensionality Reduction
- t-SNE visualization of CNN codes
- O'Reilly t-SNE Tutorial
- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
- A Fast Method to Stream Data from Big Data Sources
- ICLR 2016 Takeaways: Adversarial Models & Optimization
- Neural Networks, Types, and Functional Programming
- Automatic Differentiation - What even is it?
- Automatic Differentiation in Machine Learning - A Survey
- Using Python Itertools to Save Memory
- Jupyter Notebook Tips & Tricks
- Numpy
- Numpy Glosssary
- Super nifty for terms like:
- along the axis
- shape
- Super nifty for terms like:
- Numpy Glosssary
- Vim
- A script for bundling portable vim runtimes.
- HTTP Proxy: http_proxy=http://user:[email protected]:portnumber
- Docker Containers
- Project Jupyter