Machine Learning Career Guide
0.1.0
  • Coding
  • Machine Learning Theory
  • Machine Learning Systems
  • Applied Machine Learning
    • Canonical Micro-problems
    • Practical ML
      • Problem Framing
        • Multi-Label Learning
        • Multi-Task Learning
      • Understanding Raw Data
      • Labeling and Learning Strategies
      • Model
      • Evaluation
      • Applied Causal Inference & Uplift Modeling
      • Retraining
      • Practical Resources
      • Review Topics
      • Problems: Bias
      • MLSD Problems
    • Machine Learning Methods
    • Problem Understanding
    • Practice Problems
    • End-to-end Design
  • Product System Design
  • General Skills
  • Non-Research Topics
Machine Learning Career Guide
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  • Applied Machine Learning »
  • Practical ML »
  • Problem Framing
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Problem Framing¶

Multi-Label Learning¶

  • [mmuratarat.github.io] Metrics for Multilabel Classification

  • [towardsdatascience.com] Evaluating Multi-label Classifiers

Multi-Task Learning¶

  • [v7labs.com] Multi-Task Learning in ML: Optimization & Use Cases [Overview]

  • [medium.com] Facebook AI’s Multitask & Multimodal Unified Transformer: A Step Toward General-Purpose Intelligent Agents

  • [arxiv.org] Multi-Task Learning with Deep Neural Networks: A Survey

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