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John Collins, PhD's Projects

analyst-gpt icon analyst-gpt

GPT4 Chatbot app featuring different analysis modalities. Model: OpenAI GPT-4. Frontend: Flask, HTML, CSS, and JavaScript. Fetch API: Asynchronous data fetching and communication. pdf-lib: PDF generation/manipulation in the browser. K8s and nginx on GKE.

analystgpt icon analystgpt

"Analyst" GPT app using GPT4 and text-davinci-003. Explores impact of prompt engineering. Written in Python, using OpenAI APIs. Implemented as a web app with Python Flask framework and blueprint factory structure, Java Script, Bootstrap, CSS, and HTML. Hosted on GCP.

codellama icon codellama

The prime focus of my codellama project is to fine-tune the Code Llama 7B model and juxtapose its performance with GPT-4. Utilizing the stack outlined in README, I dive into an extensive analysis, providing a robust framework for further work with the Code Llama model.

deep-learning-finance icon deep-learning-finance

In this post I discuss some of the academic papers I have read and found useful when considering deep learning in general, and specifically its application in finance. Identical post to https://github.com/johncollinsai/dlf, but here implemented via Voila.

dlf icon dlf

In this post I discuss some of the academic papers I have read and found useful when considering deep learning in general, and specifically its application in finance. Implemented here via Flask.

finetuning-openai icon finetuning-openai

Fine-tuning of language models and prompt engineering, using the problem setting of stock price prediction based on high-frequency OHLC stock price data for AAPL.Training gpt-3.5-turbo on OHLC data to obtain raw return and log return predictions.

gpt4-website icon gpt4-website

This is the website created by GPT4, as part of my post GPT4

greg icon greg

Webapp for showcasing an AI chatbot. Greg allows a complex chatbot to be handled as a separate microservice. My project AnalystGPT (ai-analystgpt) is the chatbot microservice (note use of separate node.js email service within ai-analystgpt).

high-frequency-data icon high-frequency-data

Preparation of high frequency tick-by-tick OHLC datasets from NYSE TAQ for AAPL, JPM, and EURUSD. Python code, extended Jupyter notebook writeup. Deployed on GCP via GKE.

lstm icon lstm

This post is an abridged version of a paper I wrote some time ago and provides a thorough derivation of the LSTM network, something often skipped in finance DL papers.

nanogpt icon nanogpt

Implementation of Karpathy's NanoGPT

promptengineering icon promptengineering

Explores prompt engineering constructs. Python completions from GPT-4 using OpenAI API. Frontend: Flask, HTML, CSS, and JavaScript. Fetch API: Asynchronous data fetching and communication with the server. Deployed on gcloud as Cloud Run service.

promptevolution icon promptevolution

Prompt Evolution uses an iterative process to evolve better prompts for a domain, in this case project management of AI initiatives. As described in "Promptbreeder" (Fernando et al., 2023), it leverages a language model to generate variations of prompts, evaluates their utility, and selects the most useful prompts to propogate to next generation.

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