PythonHub
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News & links about Python programming.
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A JIT Compiler for CPython

Brandt Bucher discusses the development of a Just-In-Time (JIT) compiler for CPython. The talk delves into the challenges and intricacies of implementing a JIT compiler specifically for CPython, the default Python interpreter.

https://www.youtube.com/watch?v=HxSHIpEQRjs
Let's Code an AI Search Engine with LLM Embeddings, Django, and pgvector

Large Language Models (LLMs) can be leveraged for business applications, such as content matching and job search. William Huster demonstrates how to build a prototype application that utilizes LLMs for job search.

https://www.youtube.com/watch?v=OPy4dLHdZng
Azure-Samples / chat-with-your-data-solution-accelerator

A Solution Accelerator for the RAG pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. This includes most common requirements and best practices.

https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator
Building a Neural Network with PyTorch

Building your first neural network could seem like a formidable undertaking, but deep learning frameworks like PyTorch have made the task more accessible than ever. This article explains how to build a neural network using PyTorch.

https://haydenjames.io/building-a-neural-network-with-pytorch/
The Categories of Bugs in Python Apps

When writing a Python program, errors are inevitable. However, we can manage the types of errors we produce. Let’s explore a simple model categorizing these errors, from best to worst, and discuss how mindful tool usage can improve software quality.

https://threeofwands.com/the-types-of-errors-in-python-apps/
Generative AI for Beginners

A 12 Lesson course teaching everything you need to know to start building Generative AI applications.

https://microsoft.github.io/generative-ai-for-beginners/