A microservice for performing OCR annotation on images using Tesseract.js, containerized by Docker.
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Updated
Jul 28, 2021 - JavaScript
A microservice for performing OCR annotation on images using Tesseract.js, containerized by Docker.
Hello guys, welcome to my Data Science Portfolio. I include some knowledges I earn in my journey. I included some case study, papers, and code. Please check the readme.
🏠 California Housing Price Prediction using Machine Learning. Performed Data Cleaning, Exploratory Data Analysis (EDA), and built a Regression model to predict house prices. 🚀
A machine learning project predicting suicide risk based on multiple socio-economic and environmental factors using data mining techniques.
Contains multiple small projects on Deep Neural Network from scratch to intermediate level.
Advanced data science project for Netflix stock price prediction and analysis using Python, Pandas, NumPy, Matplotlib, Seaborn, and Plotly with interactive visualizations
This project built a binary classifier to help Alphabet Soup predict applicant success using machine learning and feature selection.
Udacity's Machine Learning Nanodegree - Project 1- Deploy a Sentiment Analysis Model
Evaluates the wpd real-space topological invariant for finite non-hermitian chains by first predicting the crop length parameter l_star using Random-forest predictors. Follows the principles provided in arXiv:2607.05900
Scalable vehicle telemetry platform with real-time data ingestion, ML-based anomaly detection, and automated alerting.
Time Series Forecasting project using the SARIMA (Seasonal AutoRegressive Integrated Moving Average) model to predict future airline passenger traffic. The project includes data preprocessing, trend and seasonality analysis, stationarity testing, SARIMA model development, forecasting, and performance evaluation using Python.
Predicts and visualizes weather data using Machine Learning and OpenWeather API.
Explainable AI for simulated cognitive profiles, interactive React/TypeScript tool with a from-scratch, interpretable logistic regression (educational, non-diagnostic)
Runs multiple.arff files through SMO and prepares results for R
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