Journal Club, Learnings and Walkthroughs

This repository contains presentations and walkthroughs of learnings from journals/articles in areas of interests for reference.

List by presentation order

• [2021-11-11] InterpretML: A Unified Framework for Machine Learning Interpretability
  • Authors: Harsha Nori et al
  • Slides
  • Supplementary links here
• [2022-02-17] Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning
  • Authors: Sebastian Raschka
  • Slides
• [2022-03-31] Hidden Technical Debt in Machine Learning Systems
  • Authors: D.Sculley et al
  • Slides
  • Supplementary links in "Resources" slide for: Interpretability Visuals, Clean Code, MLOps Tools, Courses
• [2022-06-23] Mining Root Cause Knowledge from Cloud Service Incident Investigations for AIOps
  • Authors: Amrita Saha et al
  • Slides
  • Supplementary links in "Resources" slide for: Neural Search, Knowledge Graph Embedding and Graph Neural Networks
• [2022-09-01] MLOps: Overview, Definition and Architecture
  • Authors: Dominik Kreuzberger et al
  • Slides
  • Supplemetary links in References slide on: MLOps Maturity Levels, Feature stores, OPT-175B and chronicles of its development
• [2022-11-10] Operationalizing Machine Learning: An Interview Study
  • Authors: Shankar, Garcia et al
  • Slides
• [2023-02-02] Neural Forecasting: N-BEATS & N-HiTS
  • Authors
    • N-BEATS: Oreshkin et al
    • N-HiTS: Challu and Olivares et al
  • Slides