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automl

It automates the process of creating the model. Feeding your dataset into an AutoML tool, which will automatically split the data into training and testing sets, preprocess the data, and then try out multiple machine learning algorithms (such as decision trees, neural networks, and random forests) to see which one performs best on your dataset.

bank-customers-churn

the code follows the standard machine learning pipeline: data preprocessing, EDA, handling imbalance data, train-test split, feature scaling, and model training/testing. You can see and compare the results of the SVM and XGBoost algorithms implemented.

code

Compilation of R and Python programming codes on the Data Professor YouTube channel.

covid19-public

Official data on the COVID-19 epidemic in Malaysia. Powered by CPRC, CPRC Hospital System, MKAK, and MySejahtera.

data_analysis_insight

depression_detection

Depression Detection On Social Media Using Transfer Learning

detecting-parkinson-s-disease-xgboost

XGBoost (Extreme Gradient Boosting) is a popular machine learning algorithm that is used for supervised learning problems, such as classification and regression. It is based on the gradient boosting framework and uses a series of decision trees to make predictions.

flight-insurance-analysis

Based on our analysis, we observed that consumers that travel in a short travel duration are more likely to purchase insurance, compared to a consumer who travels on a flight that has a long duration of travel.

heart_failure_prediction

About half of all Americans (47%) have at least 1 of 3 key risk factors for heart disease: high blood pressure, high cholesterol, and smoking.

machine_leaning_python

Various supervised and unsupervised machine learning models, such as regression, classification, clustering, natural language processing (NLP), artificial neural networks (ANN), and convolutional neural networks (CNN), has been utilized in training projects.

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

sentiment-analysis-about-chatgpt

Sentiment analysis that are being expressed about ChatGPT topics on Tweeter

stock_monitoring-r

This is a stock price and prediction modelling app that will assist investors on buying or selling the stocks. The stocks are based on all companies listed on S&P 500 and the price are up to date linking from Yahoo Finance server.

traffic-accident-analysis

This project we will analyze it mainly using R to determine the main causes of accidents, which is a classification task to achieve road traffic accident classification. In general, the project has two objectives: 1.Severity of Traffic Accidents Data Analysis 2.To predict Severity traffic accidents

uber_driver_churn_analysis_bigdata

Driver churn analysis based on Uber dataset using big data tools such as Hive, PySpark, Pig, Hbase, and MongoDB.