📷 Crawl and Analyze Instagram Hashtag Data: KoNLPY to gensim word2Vec & scikit-learn TF-IDF

Drilling Activity Prediction: Oil and Gas operations are dramatically affected by supply, demand and several other factors that compromise the operational planning of resources. To overcome this challenge, predictive analytics could be applied to forecast rotary rig count inside United States using time-series data.

Explore a comprehensive collection of Python programming for diverse data analysis and data science projects. This repository covers data exploration, visualization, statistical analysis, machine learning, NLP, and model deployment. Perfect for enthusiasts looking to delve into practical examples and advanced techniques.

This folder contains the basic algorithms of ML implemented with Python.

The project scope is a weather forecasting model based on behavioral analysis of the last 33 hours (hour-by-hour forecast) with Random Forest Classifier. The program automatically saves and loads the last trained model for prediction.

This repository contains basic to advanced codes related to data science and machine learning concepts using python. This is a learning endeavour using several online resources.

2024 11조 AI를 활용한 퍼스널컬러 헤어스타일 추천 서비스 Only-You

A collection of resources, code, and notes documenting my journey in Machine Learning and Data Science 📚🤖

BTAlert-AI is an application based on Machine Learning to monitor and predict application outages.

In this data set we have perform classification or clustering and predict the intention of the Online Customers Purchasing Intention. The data set was formed so that each session would belong to a different user in a 1-year period to avoid any tendency to a specific campaign, special day, user profile, or period.

An AI model built to understand the sentiments transmitted through a phrase.

This project predicts lung cancer risks using machine learning models like Random Forest, Logistic Regression, and SVM. It analyzes patient data with features such as age, smoking habits, and symptoms. Data preprocessing, visualization, and performance evaluation ensure accurate predictions for early diagnosis.

Supervised Machine Learning algorithms based simple projects [ beginner level ]

🌸 Logistic Regression Classification on the Iris Dataset

🍎 Intelligent fruit ripeness detection system using computer vision and machine learning. Implements 5 ML algorithms (SVM, Random Forest, Gradient Boosting, Logistic Regression, Ensemble) with interactive GUI for real-time predictions.

This project focuses on Human Activity Recognition (HAR) using data collected from smartphones’ embedded sensors such as accelerometers and gyroscopes.

An end-to-end machine learning pipeline for automated optical fibre fault detection, classification, and analysis using OTDR (Optical Time Domain Reflectometer) data.

Prediction of water well failure in Uganda.

Machine Learning Algorithms & Data Manipulation with Python A collection of machine learning algorithms and data manipulation techniques using Python and Scikit-learn. Covers regression, classification, clustering, and neural networks, using real email and NSL-KDD datasets for practical applications.

Emotion detection from social media texts using machine learning algorithms.