From Chaos to Cohesion: Architecting Your Own Monorepo

Build a simple monorepo using GitHub Actions as a CI/CD tool.

https://monadical.com/posts/from-chaos-to-cohesion.html

Why is the Django Admin “Ugly”?

This article discusses why the Django admin is not designed to be beautiful. It discusses the history of the Django admin and the reasons why it was designed the way it is. Some of the important points are that the Django admin is intended for internal use and not intended for building an entire front end around.

https://www.coderedcorp.com/blog/why-is-the-django-admin-ugly/

Algorithmic Trading – Machine Learning & Quant Strategies Course with Python

This course covers three advanced trading strategies. First, it focuses on Unsupervised Learning with S&P 500 data, followed by a Twitter Sentiment Investing Strategy for NASDAQ stocks, and an Intraday Strategy using the GARCH model and technical indicators to identify daily and intraday trading signals, enriching your financial skill set.

https://www.youtube.com/watch?v=9Y3yaoi9rUQ

hiyouga / LLaMA-Factory

Easy-to-use LLM fine-tuning framework (LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, ChatGLM3)

https://github.com/hiyouga/LLaMA-Factory

Wonder3D

A cross-domain diffusion model for 3D reconstruction from a single image.

https://github.com/xxlong0/Wonder3D

Build ChatGPT-like Apps with AI

If you're interested in the practical applications of AI and Large Language Models (LLMs), you'll find value in this talk and live demo. The presentation goes beyond theory to include real-world examples and best practices, including a GitHub repository packed with Python code and ChatGPT-like app examples that will help you spin up your own app.

https://sixfeetup.com/company/news/build-chatgpt-like-apps-with-ai

De4py

De4py are an Advanced python deobfuscator with a beautiful UI and a set of Advanced features that enables malware analysts and reverse engineers to deobfuscate python files and more.

https://github.com/Fadi002/de4py

Generate images in one second on your Mac using a latent consistency model

Latent consistency models (LCMs) are based on Stable Diffusion, but they can generate images much faster, needing only 4 to 8 steps for a good image (compared to 25 to 50 steps). By running an LCM on your M1 or M2 Mac you can generate 512x512 images at a rate of one per second.

https://replicate.com/blog/run-latent-consistency-model-on-mac

XAgent

An Autonomous LLM Agent for Complex Task Solving.

https://github.com/OpenBMB/XAgent

SuperDuperDB

Bring AI to your favourite database! Integrate, train and manage any AI models and APIs directly with your database and your data.

https://github.com/SuperDuperDB/superduperdb

eosphoros-ai / DB-GPT

Revolutionizing Database Interactions with Private LLM Technology

https://github.com/eosphoros-ai/DB-GPT

Raven

CI/CD Security Analyzer.

https://github.com/CycodeLabs/raven

Do not use requirements.txt

This post discusses the limitations of using requirements.txt for package management in Python projects. The author suggests using Poetry instead, which is a package manager that simplifies dependency management and provides additional features such as virtual environments and lock files.

https://quanttype.net/posts/2023-10-31-do-not-use-requirements.txt.html

lm-format-enforcer

Enforce the output format (JSON Schema, Regex etc) of a language model.

https://github.com/noamgat/lm-format-enforcer

spdustin / ChatGPT-AutoExpert

🚀🧠💬 Supercharged Custom Instructions for ChatGPT (non-coding) and ChatGPT Advanced Data Analysis (coding).

https://github.com/spdustin/ChatGPT-AutoExpert