Notable Projects
PaperLinks - AI-Enabled Application to Automate Peer-Review & Publication
Generative Artificial Intelligence for Visual Learners - A Gentle Introduction
PaperLinks - AI-Enabled Application to Automate Peer-Review & Publication
A Powerful AI-enabled application to help automate the development, formatting, and review of papers and publications. Using this powerful platform, users are able to easily gather their thoughts, work with reviewers, and prepare articles.
*** Coming Soon! ***
React ● AWS ● NLP
Building More Effective ChatGPT Prompts with Poptimizer
Generative Artificial Intelligence for Visual Learners - A Gentle Introduction
PaperLinks - AI-Enabled Application to Automate Peer-Review & Publication
In the rapidly evolving world of artificial intelligence, efficiency and precision in communication with AI models have become paramount. That’s where the Python package ‘Poptimizer’ steps in, a tool designed to improve the way we interact with OpenAI’s ChatGPT models. In this article, we’ll explore the Poptimizer library, its utility, and provide a quick demonstration of its capabilities.
Python ● OpenAI ● API
Generative Artificial Intelligence for Visual Learners - A Gentle Introduction
Generative Artificial Intelligence for Visual Learners - A Gentle Introduction
Generative Artificial Intelligence for Visual Learners - A Gentle Introduction
In this presentation I gave on generative artificial intelligence, I utilized captivating visuals to elucidate intricate concepts, catering specifically to visual learners. Through stunning imagery and simplified depictions, I demystified the workings of generative AI, making it accessible and engaging for all audiences, at all levels.
Generative AI ● NLP ● Visuals
Accelerated Information Retrieval via OpenAI and Pinecone - Tutorial
Accelerated Information Retrieval via OpenAI and Pinecone - Tutorial
Generative Artificial Intelligence for Visual Learners - A Gentle Introduction
The field of information retrieval has seen a surge recently with the onset of generative AI. Two of the most common and readily available technologies that have gained a considerable amount of popularity within the field of information extraction is OpenAI (LLM), and Pinecone (Vector Database), which when used together is sometimes referred to as the OP Stack.
Python ● OpenAI ● Pinecone
Deep Learning Architectures - A Gentle Introduction
Accelerated Information Retrieval via OpenAI and Pinecone - Tutorial
Deep Learning Architectures - A Gentle Introduction
In this presentation on deep learning architectures, I explored the fundamentals and popular models such as artificial neural networks, convolutional neural networks, recurrent neural networks, and auto-encoders, emphasizing their applications and training methodologies.
'
Deep Learning ● LSTM ● AutoEncoders
Pypercraft - A Python Package that Harnesses OpenAI to generate Full Articles
Pypercraft - A Python Package that Harnesses OpenAI to generate Full Articles
Pypercraft - A Python Package that Harnesses OpenAI to generate Full Articles
Surpassing token constraints, this application empowers users to craft full compositions comprising a Title, Introduction, Body, and Conclusion. Accessible through a user-friendly Streamlit interface or a FastAPI-powered API, the tool seamlessly merges user input with ChatGPT's contextual understanding, resulting in coherent written pieces.
Streamlit ● Python ● OpenAI
Machine Learning in Biotechnology and Life Sciences
Pypercraft - A Python Package that Harnesses OpenAI to generate Full Articles
Pypercraft - A Python Package that Harnesses OpenAI to generate Full Articles
With competition growing in the Biotechnology and Life Sciences domains, companies around the globe are looking to data-driven methods such as machine learning to optimize processes and reduce costs. In this book, we cover a comprehensive introduction to the end-to-end development of machine learning models.
Python ● AWS ● GCP
Talk: Applications of Machine Learning for Information Retrieval
Pypercraft - A Python Package that Harnesses OpenAI to generate Full Articles
Talk: Applications of Machine Learning for Information Retrieval
Ranking Models are the primary components for most modern day information retrieval systems ranging from probabilistic methods, all the way to vector space models. Within this talk, we will explore some of the most popular information retrieval methods, their underlying theory, and demonstrate their application using Python3.
Python ● Torch ● NLP
Talk: Machine Learning in Biotechnology and Life Sciences
Talk: Machine Learning in Biotechnology and Life Sciences
Talk: Applications of Machine Learning for Information Retrieval
Machine translation (MT) methods have gained a great deal of popularity in recent years within the NLP domain for numerous purposes such as language translation and data augmentation. In this talk, we will explore a Seq2Seq machine translation tutorial using Python and Torch.
Python ● Torch ● NLP
AutoTex - Automating Textract at Scale
Talk: Machine Learning in Biotechnology and Life Sciences
AutoTex - Automating Textract at Scale
An architecture for the automation of raw PDF digitization using AWS textract. S3 buckets are created as input and output locations alongside Lambda functions to detect the input of new documents. Documents are asynchronously queued using SQS/SNS, and finally logged to DynamoDB, a NoSQL database.
Python ● AWS ● DynamoDB
PyStoxx - A Stock Market Data API
Talk: Machine Learning in Biotechnology and Life Sciences
AutoTex - Automating Textract at Scale
A robust NLP API that allows users to search and retrieve current and historical data for publicly traded companies. End-points include those pertaining to sentiment, news articles, pricing history, general company information as well as known competition.
Python ● AWS ● Azure
CodeSaver - A Back-End NodeJS API to Manage Code Snippet Data
CodeSaver - A Back-End NodeJS API to Manage Code Snippet Data
CodeSaver - A Back-End NodeJS API to Manage Code Snippet Data
The purpose of this project was to develop a Node server to complement the React front-end application for CodeSaver. The API was developed to function with react on the front-end, and MongoDB as the database. The API supports full CRUD operations with a number of fully documented different end-points.
NodeJS ● JavaScript ● MongoDB
iKNOW - A Stock Market Forecasting
CodeSaver - A Back-End NodeJS API to Manage Code Snippet Data
CodeSaver - A Back-End NodeJS API to Manage Code Snippet Data
The purpose of this project is to utilize the latest developments in feature engineering to identify features with important predictive trends. Thousands of company websites were scraped, and vital information was regarding 10K filings were retrieved. We propose here a novel method to identify stock trends within the perceived features.
Python ● DynamoDB ● AWS
BLTC - Bidirectional LSTM Text Classifier
CodeSaver - A Back-End NodeJS API to Manage Code Snippet Data
CodeSaver - A Front-End Code Snippet Management Web App.
This project concerns the development of a bidirectional text classifier for the purposes of improving previously existing classifiers for the same toxic comment dataset. The addition of a bidirectional and convolutional layer showed a significant improvement both with the loss as well as the accuracy.
Python ● Jupyter Notebook ● Keras
CodeSaver - A Front-End Code Snippet Management Web App.
CodeSaver - A Front-End Code Snippet Management Web App.
CodeSaver - A Front-End Code Snippet Management Web App.
CodeSaver is an application designed for the purpose of helping developers of various computer languages save, find and recycle their code with ease. The platform includes a number of features that allow users to find, read, and edit code saved in snippets. Users can also import snippets from and export snippets to GitHub via the GitHub Gists API.
React ● JavaScript ● Firebase
eLysis - QAC Potency Prediction using ML
CodeSaver - A Front-End Code Snippet Management Web App.
eLysis - QAC Potency Prediction using ML
The purpose of this project was to develop a predictive model using some of the latest developments in machine learning to predict potency of compounds of interest to combat MRSA infections. Vital data was collected pertaining to thousands of MRSA-effective and -ineffective compounds. Trends were identified, and a model with nearly 92% accuracy was developed.
Python ● MySQL ● AWS
QUORUM - Machine Learning to Combat MRSA
CodeSaver - A Front-End Code Snippet Management Web App.
eLysis - QAC Potency Prediction using ML
I co-founded Quorum Therapeutics in an effort to investigate the use of Machine Learning and Deep Learning for the identification of compounds to combat sepsis. Our program identified and designed a number of novel compounds, of which one candidate, QRM-005 showed optimal efficacy. Clinical studies are currently underway to confirm our data-driven strategies.
Python ● Tensorflow ● AWS