Python Weekly (Issue 651 May 23 2024)

Python Weekly - Issue 651

May 23, 2024

Python Weekly

Welcome to issue 651 of Python Weekly. Let's get straight to the links this week.

From Our Sponsor 

Articles, Tutorials and Talks

Learn college Precalculus from an experienced university mathematics professor. You will also learn how to implement all the Precalculus concepts using the Python programming language.

Understand the exact structure with working implementation of the Llama 3 model.

NeMo Curator, which is part of NVIDIA NeMo, offers workflows to download and curate data from various public sources out of the box such as Common Crawl, Wikipedia, and arXiv. It also provides flexibility for developers to customize data curation pipelines to address their unique requirements and create custom datasets. This post walks you through creating a custom data curation pipeline using NeMo Curator. 

Getting data out of Apache Kafka is easy if you know how, so let's go through an example step-by-step. In this walkthrough we take you through the process of creating a simple Kafka Consumer using the Quix Streams library. 

A tale of how I accidentally stumbled upon some interesting tech over time.

Learn how to fine tuning LLM models. This course will teach you fine tuning using using QLORA and LORA, as well as Quantization using LLama2, Gradient and the Google Gemma model. This crash course includes both theoretical and practical instruction to help you understand how to perform fine tuning.

A simple tutorial on creating beautiful maps using the prettymapp library.

In this guide, we will explore the core principles of unit testing, delve into Pytest's powerful capabilities, and equip you with the knowledge and skills to write clean, maintainable, and effective tests.

The post details the author's process for building interactive embedding visualizations from user data, such as representing entities like words, products, or users as points in a high-dimensional space and projecting them down to 2D or 3D for visual exploration. It covers the entire workflow, from data preparation to dimensionality reduction techniques and interactive visualization implementation.

The blog post explains how to create a dynamic GitHub profile README that displays up-to-date stats and information by leveraging GitHub Actions to periodically fetch data and generate a new README file. 

The post discusses potential security risks and "footguns" that can arise when using Docker containers, signals, and shells together in a development environment. It highlights how certain combinations of these tools can inadvertently grant excessive permissions or expose sensitive data, emphasizing the need for caution and proper configuration.

Interesting Projects, Tools and Libraries

A pure NumPy implementation for Llama 3 model.

Open source Python SDK for agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks like CrewAI, Langchain, and Autogen.

llama3 implementation one matrix multiplication at a time.

This guide is designed for technical teams interested in developing basic conversational AI solutions using Retrieval-Augmented Generation (RAG).

Open-source, accurate and easy-to-use video speech recognition & clipping tool, LLM based AI clipping intergrated.

An AI-Powered Tool for Automated Test Generation and Code Coverage Enhancement!

New Releases

Upcoming Events and Webinars

There will be a talk, Python, why are you like this? Python Gotchas and how to avoid them.

There will be a talk, Apache Arrow - Exploring the tech that powers the modern data (science) stack.

There will be a talk, NoSQL to SQL.. without ETL? A look at Azure Synapse Link.

There will be following talks

  • Advancing one second at the time: Wolt's path optimizing efficient delivery platforms

  • Design data pipeline with GenAI

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