Makes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & tracking

common used Recommend Baseline Model, including the traditional statistical model, and the Nerual Network Model. Focus on the SRS (Sequential Recommend System).

2019语言与智能技术竞赛，信息抽取任务的基线模型python3代码。模型包括：关系抽取（多标签模型）和实体抽取（序列标注模型）

A retail analytics capstone that converts transactions into a calendar intelligence system. It quantifies day-of-week and monthly seasonality, builds a baseline expected revenue model, detects event-like spike days using robust residual z-scores, and explains spikes via transactions, units, AOV, and category mix, with a Streamlit dashboard+exports.

Movie Recommendation System

Automatically generate a pdf report containing feature importance, baseline modelling, spurious correlation detection, and more, from a single command line input for any given ML CSV file

Fake news headlines in the Tamil regional language.

This is a Time Series Forecasting and Regression solution to project the no. of pick-ups at and around a given region at a given time in the city of New York, USA.

Baseline models for HIPE-2022

The baseline code for the CLPsych 2021 Shared Task.

Implemented Linear Regression using scikit-learn to predict housing prices. Evaluated model performance using R² score (~0.64) and residual distribution analysis to assess prediction errors and regression assumptions.

Baseline identification for Energy Performance Contracts

This repository documents my journey participating in the ARC Prize 2026 on Kaggle.

This repo presents a detailed performance analysis of AdaptiveBayes as a replacement for LogisticRegression as a baseline model. Results are based on classic ML datasets and a wide range of large-scale benchmarks.

architecture performance on CIFAR10 without tricks

All asignment from data science bootcamp by Dibimbing.id

Cleans historical LCD weather files from NOAA and returns an hourly .CSV file

Multinomial logistic regression modeling used to determine influential factors in nicotine usage status

Engineered GAF-Net, an enhanced YOLOv8-based model for multi-disease corn leaf detection, integrating GSConv and FASF modules to boost feature extraction and localization accuracy. Achieved efficient, real-time performance through optimized training and inference on annotated agricultural datasets.

Implementation for the Classification and Evaluation models as part of the Introduction to Machine Learning (COMP90049) course at The University of Melbourne.