Week 22 - June 21

Tuesday 6/1

Machine learning in python with scikit-learn end of module 3. Hyperparameter tuning

Reinforcement Learning Specialization - C2W3 - Temporal Difference for Control - start

Wednesday 6/2

SHAP: An introduction to explainable AI with Shapley values, Be careful when interpreting predictive models in search of causal insights

Machine learning in python with scikit-learn module 4. Linear models

Thursday 6/3

Talk (30’) from Michael Bronstein on Geometric Deep Learning - permutations invariant is a domain research I could use

Machine learning in python with scikit-learn end of module 4. Linear models

Friday 6/4

Reinforcement Learning Specialization - C2W4 - Planning, Learning and Acting

End of course 2 of Reinforcement Learning Specialization

Week 23 - June 21

Monday 6/7

Reinforcement Learning Specialization - C3W1 - On-policy Prediction with Approximation

Thursday 6/10

Reinforcement Learning Specialization - C3W2 - Constructing Features for Prediction

Friday 6/11

Machine learning in python with scikit-learn module 5. Decision tree models

Reinforcement Learning Specialization - C3W3 - Control with Approximation

Week 24 - June 21

Monday 6/14

Reinforcement Learning Specialization - C3W4 - Policy Gradient

Reinforcement Learning Specialization - C4W1 - start of course 4. A Complete Reinforcement Learning System (Capstone) - week 1 to week 4

Wednesday 6/16

Reinforcement Learning Specialization - C4W4 - Milestone 3: Identify Key Performance Parameters, C4W5 - Milestone 4: Implement your agent

Thursday 6/17

Reinforcement Learning Specialization - end of C4W5 - Milestone 4: Implement your agent

Friday 6/18

Reinforcement Learning Specialization - C4W6 - Milestone 5: Submit your Parameter Study!

End of Specialization

Week 25 - June 21

Monday 6/21

Machine learning in python with scikit-learn module 6. Ensemble of models

RL Course by David Silver Integrating learning and planning (lecture 8)

Thursday 6/24

Machine learning in python with scikit-learn module 7. Evaluating model performance -End of this course

Week 26 - June 21

Monday 6/28

AI Tech watchfulness in Manufacturing using Arxiv Sanity Presever

Paper reviewed on arxiv about local post-hoc explanations for predictive process monitoring in manufacturing. arXiv:2009.10513v2. SHAP, ICE and why this approach makes sense in manufacturing domains.

Wednesday 6/30

Survey Paper reviewed on Journal of Manufacturing Systems about Deep learning for smart manufacturing: Methods and applications. j.jmsy.2018.01.003. Review use of deep learning algorithms: CNN, RBM, auto encoders, RNN and applications for smart manufacturing: quality inspection, fault assessment, defect prognosis (RUL). Unfortunately prescriptive usage are missing. Points to multiple references origins of these algorithms and applications. Great survey paper!