Project | Descrption | Images | Status | Code status |
---|---|---|---|---|
Social distancing simulator | Simulating disease spread in a graph-based model that allows agent interaction. | ![]() |
Active | |
Reinforcement learning using Keras | Building various reinforcement learning approaches from scratch in Keras and Tensorflow 2.3. | ![]() ![]() |
Active | |
Multisensory integration models | Comparing possible mechanisms of multisensory integration in the mammalian brain using deep neural networks. | ![]() |
Backburner | |
AudioDAG | Lazy, DAG based stimulus builder for psychophysics stimuli. Not just for audio. | ![]() |
Backburner | |
PsychometricCurveFitting | Psychometric curve fitting for MATLAB and Python. | ![]() |
Backburner | |
Microservices for Sklearn models | Playing with REST/GRPC/Minio/Docker/Kubernetes, etc. to build basic microservices hosting Sklearn models. | Backburner | ||
IncrementalTrees | Out-of-core fitting of Sklearn forest models using Dask. | Inactive | ||
Epileptic Seizure prediction | Predicting epileptic seizures in humans using machine learning and EEG data. Publications: Brain, Epilepsia, Kaggle blog, Mathworks blog | ![]() |
Completed | |
Drift diffusion modelling | Decision modelling using drift multi-channel drift diffusion models with dynamic decision boundaries, adaptation, etc. | ![]() |
Inactive | |
Integer sequence learning | Predicting integer sequence functions from few examples. Publications: Kaggle blog | ![]() |
Completed |
garethjns / kaggle-redhat Goto Github PK
View Code? Open in Web Editor NEWEarly entry for Kaggle compeition (https://www.kaggle.com/c/predicting-red-hat-business-value) and script/notebook for basic exporation of the two datasets