This project develops an ML binary classification model to predict phishing webpages.
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Updated
Apr 11, 2023 - Jupyter Notebook
This project develops an ML binary classification model to predict phishing webpages.
Writeup on classification model for predicting outcomes of NFL games, focusing on explainability. (+ project writeup)
Predict which powerlifters will have the highest one-rep-max deadlift
Machine Learning Final Project - December 04, 2021
This project provides a performance evaluation of credit card default prediction. Thus different models are used to test the variable in predicting the credit default and we found Random Forest Classifier performs the best with a recall of 0.95 on the test set.
This project implements an ML regression model for predicting cancer death rate in US.
A reusable codebase for fast data science and machine learning experimentation, integrating various open-source tools to support automatic EDA, ML models experimentation and tracking, model inference, model explainability, bias, and data drift analysis.
This project is a machine learning competition hosted on Kaggle platform, focused on forecasting Walmart's monthly and quarterly sales. We tasked with developing advanced predictive models to accurately predict Walmart's sales, taking into account various factors such as historical sales data, macroeconomic indicators, and local market conditions.
Machine Learning Individual Project - November 23, 2021
Developed an efficient system to empower retailers with profitable insights & maintain a competitive edge in the dynamic retail industry.
Study on the performance of pre-trained models (VGG16, EfficientNetb0, ResNet50, ViT16) with weight fine tuning, as well as classical ML algorithms (Naive Bayes, Logistic Regression, Random Forest) on a dataset of 6.806 fungi microscopy Images utilizing Pytorch.
The Fraud Detection project aims to improve identification of fraudulent activities in e-commerce and banking by developing advanced machine learning models that analyze transaction data, employ feature engineering, and implement real-time monitoring for high accuracy fraud detection.
An application of the WhizML codebase for an analysis of cardiovascular disease risk.
A proof-of-concept for the implementation of an early fault detection system in oil wells, designed to enhance operational efficiency and reduce costs.
Example projects for Arthur Model Monitoring Platform
The official Python library for Openlayer, the Continuous Model Improvement Platform for AI. 📈
Capture fundamentals around ethics of AI, responsible AI from principle, process, standards, guidelines, ecosystem, regulation/risk standpoint.
Explaining Trees (LightGBM) with FastTreeShap (Shapley) and What if tool
Java client to interact with Arize API
CrysXPP: An Explainable Property Predictor for Crystalline Materials (NPJ Computational Materials - 2022)
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