Summary#

Mining, classification and prediction of data using various techniques and models like Decision Trees, Association Rules, and Neural Networks.

Key Strengths#

• Interpreting demographics, association rules and feature selection to determine significant features for classification
• Tuning hyperparameters of models to ensure optimal accuracy metrics
• Training various models including Logistic Regression, Decision Trees, Random Forest Classifiers, Naive Bayes Networks, Support Vector Machines, and Neural Networks to predict and classify previously unknown data

Related Projects#

• Analyzing Covid-19 Data to Predict Long Covid-19 Cases
• Recognizing Temporal Patterns using an Echo State Network
• CIFAR-10 Image Classification
• Classifying Digits with Logistic Regression
• Titanic Survival Prediction