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This repo contains a collection of books, academic papers, blog posts, videos and courses I have consumed over the years and found insightful. The topics mostly involve ML, ML-Ops and software development in general. I have tried to provide a source for most resources, but some books/courses are not available for free.

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Knowledge resources - My personal collection

The following is a collection of books, academic papers, blog posts, videos and courses I have consumed over the years and found insightful. The topics mostly involve ML, ML-Ops and software development in general. I have tried to provide a source for most resources, but some books/courses are not available for free.

Machine Learning

  • General (Covers many areas)
    • 20 Popular Machine Learning Metrics. Part 2: Ranking, & Statistical Metrics [Blog]
    • The retail “bible” - Introduction to algorithmic marketing [Book]
    • Everything ML and reference papers. Can be used when trying to find reference material for a specific area / use-case [Github collection]
    • Massive resource on eveything ML/DL [Website]
    • Awesome machine learning papers [Github collection]
    • Fashion AI [Github collection]
    • Fashion Meets Computer Vision: A Survey [Paper]
    • Theoretical Foundations of Graph Neural Networks [Video]
    • Why is Object Detection so Messy? [Blog]
    • A guide to dynamic pricing algorithms [Blog]
    • Advertising papers [Github collection]
    • Optimized Cost per Click in Taobao Display Advertising [Paper]
  • Recommender systems
    • How Does the Recommendation System Work on Tmall? [Blog]
    • Awesome RecSys Works [[Github collection]](Awesome RecSys Works)
    • Recommender Systems [PapersWithCode]
    • TensorFlow Recommenders [Website]
    • Collaborative Filtering using Deep Neural Networks (in TensorFlow) [Blog]
    • Neural Graph Collaborative Filtering [Paper]
    • Neural Collaborative Filtering [Paper]
    • Wide & Deep Learning for Recommender Systems [Paper]
    • Learning Item-Interaction Embeddings for User Recommendations [Paper]
    • Next Basket Recommendation with Neural Networks [Paper]
    • Deep Learning based Recommender System: A Survey and New Perspectives [Paper]
    • Recommender Systems — It’s Not All About the Accuracy [TODO]
  • Search & Ranking
    • Applied Machine Learning for Ranking Products in an Ecommerce Setting [Video]
    • Smart rankings at Farfetch [Blog]
    • Cross-Lingual End-to-End Product Search with Deep Learning [Blog]
    • Relevant Search [Book]
    • What is Learning to Rank? [Blog]
    • How is search different than other machine learning problems? [Blog]
    • Search at Farfetch - A glimpse of Semantic Search [Blog]
    • Cross-Lingual End-to-End Product Search with Deep Learning [Blog]
    • Neural Search Frameworks: A Head-to-Head Comparison [Blog]
    • Vector Podcast [Podcast]
  • NLP
    • In-depth article on self-attention [Blog]
    • A Comprehensive Guide to Neural Machine Translation using Seq2Seq Modelling using PyTorch. [Blog]
  • Other
    • Self-Organizing Intelligent Matter: A Blueprint for an AI Generating Algorithm [Paper]

MP-Ops

  • Machine Learning Design Patterns [[Book]]
  • Resources for GCP Professional Machine Learning Engineer certificate [Github collection]
  • Massive resource on everything ML-Ops [Website]

Software development

  • The pragmatic programmer [Book]
  • Effective Python: 90 Specific Ways to Write Better Python [Book]
  • The Frontend Developer Career Path [Course]
  • A visual debugger for Jupyter [Blog]

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This repo contains a collection of books, academic papers, blog posts, videos and courses I have consumed over the years and found insightful. The topics mostly involve ML, ML-Ops and software development in general. I have tried to provide a source for most resources, but some books/courses are not available for free.

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