This Lummetry.AI public repository for the 2020 Stanford XCS229ii workshop. Lummetry.AI (Knowledge Investment Group SRL) team workshop participation is sponsored through grant no 9/221_ap2/23.12.2019/SMIS-129090 for the project "SEER - Electronic System for the automated evaluation and feedback of business scenarios based on predictive analytics and Artificial Intelligence" under the financing programme Competitiveness Operational Program (COP) Action 2.2.1 - "Supporting the growth of added value generated by the ICT sector and innovation in the field through the development of clusters" co-financed by the European Regional Development Fund
The following content is made available under GNU General Public License ("GPL") v 3.0 and is mainly the creation of the Lummetry.AI team consisting of Andrei Ionut Damian and Laurentiu Gheorghe Piciu. No proprietary content of Stanford University or Stanford Center of Professional Development (SCPD) has been made public
- 2020-05-01 - Created the plan for the public dissemination of results that do not infrige any copyright regulation of the XCS229ii workshop
- 2020-10-20 - Published (Open Source v3 license) the initial commit of the repo
- 2020-10-20 - Added "gated.py" - the simple gated unit is the first primitive that we will use in our final project that develops and applies in real use-cases our own state-of-the-art research called "Multi Gated Unit"
- 2020-11-19 - RL (policy gradient in tensorflow) Cartpole-v0 experiment
- 2020-12-20 - Added all the MGU work