Restricted Boltzmann Machines
A Beginner's Tutorial for Restricted Boltzmann Machines - Deeplearning4j- Open-source, Distributed Deep Learning for the JVM
t-distributed stochastic neighbor embedding - Wikipedia
Lecture 10 Reinforcement Learning I
PyBrain - a simple neural networks library in Python
- Provides a design tool for visual programming allowing you to connect together data preparation, algorithms, and result evaluation
together to create machine learning “programs”. Provides over 100 widgets for the environment and also provides a Python API and library for
integrating into your application.
- Weka explorer
- A graphical machine learning workbench. It provides an explorer that you can use to prepare data, run algorithms and review results. It
also provides an experimenter where you can perform the same tasks in a controlled environment and design a batch of algorithm runs that could
run for an extended period of time and then review the results. Finally, it also provides a data flow interface where you can plug algorithms
together like a flow diagram. Under the covers you can use Weka as a Java library and write programs that make use of the algorithms.
- A web service where you can upload your data, prepare it and run algorithms on it. It provides clean and easy to use interfaces for
configuring algorithms (decision trees) and reviewing the results. The best feature of this service is that it is all in the cloud, meaning that
all you need is a web browser to get started. It also provides an API so that if you like it you can build an application around it.