Obsidian is really cool tool for notetaking. Here’s an Open source plugin that allows you to create branching possibilities in text generation, visualised as a graph, using OpenAI LLM capabilities. Written in TypeScript. 
Today I made my first PyPi package. This is for calculating the W Randomness Coefficient of a set of algorithms on a suite of Machine Learning benchmarks. This quantifies the uncertainty of different algorithms’ ranking due to the presence of testing on different random seeds. Just use pip install wrandai.
I wanted to play music in my room using the posters of album art. My project uses a camera to detect when I ‘click’ on the album art on my wall using my hand to play the corresponding music on my speakers. This is an ongoing project; the next step is to put the software on a standalone device. - Uses 3D CNNs to detect hand landmark positions on video footage - Recognises simple gestures to control user interface. - Object detection and google vision API to detect album art on wall and search for associated album. - Spotify API to play music on speakers.
This project uses the openai api’s to recognise voice input and convert the audio to text; generate a poem from the trigger words then play the poem in a generated voice. As this uses the research purpose only apis it won’t be released to the public. Nethertheless, this is still pretty cool that it’s really easy to build something like this or I’m one of these 10x coders you hear so much about. Either way, this demonstrates the promise of AI technology in case you hadn’t heard about this little thing called machine learning. 
I built a cryptocurrency wallet on a Raspberry Pi. I modified a custom reinforcement learning environment to train a deep belief network to trade cryptocurrencies. This is also ongoing; algorithmic trading is hard.
This project contains a script for extracting arxiv paper links in twitter likes and extracting them into a reading list notion table.