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advanced-solidity

Create an ERC20 token and a crowdsale for funding

airline-sentiment-analysis

This sentiment analysis project aims to classify US airline tweets as positive or negative. It explores both classical ML and deep learning approaches. The LSTM outperforms XGBoost with an AUC score of 0.9462, despite a slightly lower accuracy. The AUC metric highlights LSTM's efficacy in handling imbalanced datasets.

allstate-claims-severity

This repository features code for the Allstate Claims Severity Kaggle competition, utilizing Python, primarily XGBoost, and LightGBM for predicting insurance claim losses. Through preprocessing and hyperparameter tuning, LightGBM attains the best validation MAE of 0.4157, selected for test dataset predictions and competition submission.

anomaly-detection-using-autoencoders

Autoencoder Neural Network is trained on credit card transaction data to detect anomalous transactions in near real time using flask api

bert-question-answering-app

This project demonstrates a user-friendly web application that uses a pre-trained BERT-based model to answer questions based on a given passage. The app is built using Python, the transformers library for BERT, Flask for the web framework, and HTML/CSS for the interactive user interface.

case_study

casestudyproposal

Case Study on Apple's Apple Pay

churn-analysis-and-prediction

Telecom Churn Analysis: Predicting customer churn using ML. Best model was XGBoost with 81.92% accuracy. SHAP analysis revealed top features. Results and insights visualized in Tableau

clustering-crypto

The purpose of this project is to help simply the cryptocurrency space by generating a list of tradable currencies and grouping these currencies into particular categories. Data Preprocessing with PCA and Clustering using K-Means

credit-card-default

This project was created to predict credit card defaults based on customer profiles, achieving a high ROC AUC score of 0.7882 The model analyzes borrower information, such as age, income, and financial indicators, to identify customers at risk of defaulting. The model was deployed to streamlit as a web app.

crypto-sentiment

The purpose of this assignment is to apply Natural Language Processing techniques to analyze the sentiment of Bitcoin and Ethereum using recent news articles pulled from the newsapi.

cryptoright

CryptoRight Blockchain Copyright System

cv_mobile_app

deploying-machine-learning-models

Code for the online course "Deployment of Machine Learning Models"

financial-planner

income-prediction-case-study

Built Simple Random Forrest Classification model, using the data provided by UCI, that determines if a person makes over $50K a year.

jacobj215

Config files for my GitHub profile.

jacobj215old.github.io

learnopencv

Learn OpenCV : C++ and Python Examples

license-renewal-status-using-neural-networks

The objective of this project is to assess given various features whether a customer's business license should be issued, renewed or cancelled

llm-qna-chat-bot

This is a Generative AI powered Question and Answering app that responds to questions about your uploaded file. Here we utilize HuggingFaceEmbeddings and OpenAI gpt-3.5-turbo

lstm-stock-predictor

For this project, I used deep learning recurrent neural networks to model bitcoin closing prices

lung-cancer-segmentation

Developed a Lung Cancer Segmentation model using the U-Net architecture and PyTorch Lightning framework. Achieved an unimpressive dice loss of 0.0247 more work is required.

machine-learning-guide

The idea behind this Intro to Machine Learning Guide was to initially create a list of resources to provide to my students. This eventually morphed into a comprehensive guide that will eventually cover everything from Linear Regression to Neural Networks

martian-auction

Martian Auction using smart contracts

melbourne-housing-price-prediction

The purpose of this notebook is to display some of the most common, practical and powerful machine leaning techniques and applications used to solve simple data science problems. Here we are using the Melbourne housing clearance data from Kaggle to predict housing prices.

myers-briggs-nft-web-app

Project_3

opencv

Open Source Computer Vision Library

optical-character-recognition-webapp

This project is a web application that uses YOLOv5 and InceptionResNetV2 models for license plate detection and Optical Character Recognition (OCR) text extraction. The web applications were built using streamlit and flask

password-generator

This a password generator created using the django framework