> For the complete documentation index, see [llms.txt](https://www.mlcompendium.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.mlcompendium.com/readme.md).

# The Machine & Deep Learning Compendium

This page introduces the Machine and Deep Learning Compendium and where it lives.

A makeover of this book was done. [How it was done](https://github.com/orico/www.mlcompendium.com/tree/main/readme/makeover.md).

<figure><img src="https://83674056-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-Mgd48oS5_duTKOVE_Et%2Fuploads%2FouHuBLPAPIHcXpZQGP5K%2Fimage.png?alt=media&amp;token=31ec0b47-2d6c-49ee-914e-592eed426e5d" alt=""><figcaption><p>The Machine and Deep Learning Compendium.</p></figcaption></figure>

Covering **502 topics**, the ML and DL Compendium includes summaries, links, and articles across a wide array of subjects, including LLMs. These range from modern machine learning algorithms and deep learning techniques to specialized areas like NLP, audio processing, computer vision (classic and deep), time-series analysis, anomaly detection, and graphs. It also goes deep into strategic themes like data science management, team building, and practical essentials like product management, design, and technology stacks from a data science perspective. The [Ops](/ops/ops.md) half of this book covers how you build, ship, govern, and run the system.

The ML and DL Compendium is completely open and now lives on [GitHub](https://github.com/orico/www.mlcompendium.com/) (please star it!). Driven by my belief in knowledge-sharing and education, this project will always remain not-for-profit and free.

{% embed url="<https://github.com/orico/www.mlcompendium.com>" %}
The ML and DL Compendium official GitHub repo
{% endembed %}

The Machine and Deep Learning Compendium began as a personal project: a curated list of resources I maintained in a private Google document for my own learning. That document has now evolved into this new interface, and I am excited to share it as an educational tool to help others learn and connect with the brilliant authors I have summarized, quoted, and referenced.

I envision it as a go-to resource for learners of all levels, whether you are an industry data scientist, an academic, or just starting out. It is designed to save you countless hours of searching and filtering through content, providing a streamlined path to invaluable authors and resources you can further support.

<figure><img src="https://83674056-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-Mgd48oS5_duTKOVE_Et%2Fuploads%2FH5MeNsH1ACCNTJ0qq1iM%2Fimage.png?alt=media&amp;token=2a94f84c-1821-4fd1-b974-3194a48d389b" alt=""><figcaption><p>The Machine and Deep Learning Compendium.</p></figcaption></figure>

Let us work together to support the community, amplify the voices of authors, and democratize education. If you spot something that could be improved, feel free to contribute via [GitHub](https://github.com/orico/www.mlcompendium.com/tree/master) or [reach out](https://www.linkedin.com/in/cohenori/) to me directly.

{% embed url="<https://cohenori.medium.com/the-last-machine-deep-learning-compendium-youll-ever-need-dc973643c4e1>" %}
The ML Compendium article, by Dr. Ori Cohen
{% endembed %}

Many thanks,

Dr. Ori Cohen

[My Website](https://www.oricohen.com/) | [Medium](https://medium.com/@cohenori) | [LinkedIn](https://www.linkedin.com/in/cohenori/) | [ML Compendium](http://www.mlcompendium.com/) | [Ops](/ops/ops.md) | [State of GenAI](https://stateofgenai.com/) | [State Of MLOps](https://stateofmlops.com/) |


---

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