The Algorithms Project, LLM Course from IIT Delhi, Parallel Computing Course from Stanford University

This week's agenda:

• Open Source of the Week - the Algorithms project
• New learning resources - LLM course from IIT Delhi, tuning LLMs, webR for Quarto tutorial, and more
• Book the week - Geospatial Data Science Essentials by Milan Janosov

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Open Source of the Week

This week's edition open source focus is The Algorithms project. This community project provides information about open-source algorithms and learning data structures and their implementation in a variety of programming languages.

The project website has an algorithm search that returns the corresponding implementation by programming languages. For example, the search for linear regression returns the following results:

This includes code snippets in different languages, such as Python and Rust, as well as examples of full implementation in Python, R, and Julia:

The project is under an MIT license and welcomes contributions.

New Learning Resources

Here are some new learning resources that I came across this week.

Large Language Models

Large Language Models is a new course by Prof. Tanmoy Chakraborty from IIT Delhi and researchers from IBM Research, Microsoft, and DA-IICT. This full semester course (26 lectures) covers topics such as:

• Introduction to NLP
• Word2Vec
• Core deep learning models for NLP applications (RNN, LSTM, GRU, etc.)
• Tokenizing
• Instruction tuning
• Vision Language Models

More details are available on this post and on the course website.

Fine-Tuning Large Language Models

The following one-hour workshop by Oren Sultan provides an introduction to fine-tuning large language models. The workshop covers topics such as fine-tuning approaches, prompt engineering, RAG methods, and demo fine-tuning process using LLaMA 2-7b-chat LLM.

Easiest Way to Fine-Tune LLAMA-3.2 and Run it in Ollama

With the release of LLAMA-3.2, here is a short tutorial for fine-tuning the model and executing it with Ollama:

Adding Multiple Choice Quiz to Quarto Live Tutorials

Are you using Quarto for education? You should check this great tutorial by Yanina Bellini Saibene about how to set multiple-choice quizzes with Quarto documentation:

More details are available on Yanina's post.

Stanford CS149 - Parallel Computing

Stanford University released a new CS course focusing on parallel computing last week. The course, taught by Prof. Kayvon Fatahalian and Prof. Kunle Olukotun, focuses on the foundations of modern parallel computing systems design. This includes different techniques for parallel programming to effectively utilize machines' available resources.

More details are available on the course website.

CUDA Programming Course – High-Performance Computing with GPUs

More on parallel computing - If you are looking for a resource to learn CUDA, here is a new course by Elliot Arledge and freeCodeCamp. This 12 hours course covers the foundations of programming with CUDA, and it includes topics such as:

• Introduction to CUDA
• Deep Learning Ecosystem
• Intro to GPUs
• Writing your First Kernels
• PyTorch Extensions

Book of the Week

This weekend, I enjoyed reading Milan Janosov 's new book - Geospatial Data Science Essentials. While most of the resources I know for GIS analysis are in R, Milan is one of the main people I follow on LinkedIn who creates content about GIS analysis with Python.

The book covers the following topics:

• Foundation of geometries
• Vector and GIS data in Python
• GIS data visualization
• Map projections
• OpenStreatMap data ??
• Stats and ML applications for GIS data

The book has an online version, and it is available to purchase on Amazon:

Have any questions? Please comment below!

See you next Tuesday!

Thanks,

Rami

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