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The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems.
An agent-based situated language learning simulation that focuses on lexical learning and grounding, featuring a unigram syntax structure and a CFG-based semantic grammar. Created as a MSc thesis project, using python.
A three-step approach towards experimental brain-computer-interfaces, based on the OCZ nia device for EEG-data acquisition and artificial neural networks for signal-interpretation.
Brainiac, Is C/C++ Libraries, Programs, And Python, And Lua Scripts For Neural Networking And Genetic Programming, In An Attempt To Create A "Glue-It-All-Together" Project, Striving Towards General Artificial Intelligence
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A low code unified framework for computer vision and deep learning
Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers.
There are three libraries in this opensource set.
- Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms.
- Monk Object Detection -...