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Machine learning cheat sheets

Machine learning cheat sheets on Sefism, written by Tauseef Fayyaz: every concept in plain words, why it is used and the pitfall that catches people out.

  • 76 sheets
  • 5120 concepts

Free to learn. Credits keep it fair.

Reading is free. Adding a roadmap, keeping a cheat sheet or asking Tauseef a question uses credits, which only make sure the platform goes to people who are actually learning.

  • 15creditswhen you join
  • 1stroadmapfree to add
  • Morecreditson request, as you learn

Specialise

6

Go deep in one area of engineering.

  • Cheat sheet · Specialise

    Machine learning cheat sheet

    Data, models, deep learning.

    Chapters

    1. 1Python for data
    2. 2The maths you need
    3. Data cleaning and feature engineering

    + 5 more

    • 8 chapters
    • 69 concepts
    Opens with credits
  • Cheat sheet · Specialise

    Data science cheat sheet

    Statistics, pandas, ML, experiments.

    Chapters

    1. 1Code for data: Python or R
    2. 2Statistics and probability you use
    3. SQL for data work

    + 7 more

    • 10 chapters
    • 76 concepts
    Opens with credits
  • Cheat sheet · Specialise

    MLOps and LLMOps cheat sheet

    Ship, serve and monitor models.

    Chapters

    1. 1From notebook to package
    2. 2Data and model versioning
    3. Experiment tracking and the registry

    + 7 more

    • 10 chapters
    • 70 concepts
    Opens with credits
  • Cheat sheet · Specialise

    PyTorch cheat sheet

    Tensors, autograd, nn.Module, training loops, data loading, GPUs, mixed precision, torch.compile, DDP and export in PyTorch.

    Chapters

    1. 1Tensors
    2. 2Autograd
    3. Models with nn.Module

    + 6 more

    • 9 chapters
    • 59 concepts
    Opens with credits
  • Cheat sheet · Specialise

    Hugging Face cheat sheet

    The Hub, transformers, tokenisers, datasets, fine-tuning, LoRA, quantisation, inference and embeddings with the Hugging Face libraries.

    Chapters

    1. 1The Hub
    2. 2Running models with transformers
    3. Tokenisers

    + 5 more

    • 8 chapters
    • 51 concepts
    Opens with credits
  • Cheat sheet · Specialise

    MLflow cheat sheet

    Experiment tracking, the tracking server, models and signatures, the Model Registry with aliases, serving, evaluation, GenAI tracing and MLOps.

    Chapters

    1. 1Tracking experiments
    2. 2Autologging, search and the UI
    3. Tracking server and stores

    + 6 more

    • 9 chapters
    • 65 concepts
    Opens with credits

Browse the cheat sheets by topic

Each of these is its own page: the foundations shelf, the career shelf, the sheets that are open end to end. The filters above do the same thing without a page load.

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