Machine Learning Final Projects⌗
1. Unsupervised Learning and Dimensionality Reduction⌗
Examine K-means and dbscan PCA for Enhanced Logistic Regression Performance: Develop a dimensionality reduction model using PCA to evaluate and enhance the performance of logistic regression. Machine Learning Mastery - PCA tutorial
2. Time Series Analysis⌗
Basics of Time Series Analysis Application with ARIMA models Classifying Stress Conditions using TDA: Extract topological features to classify physiological signals under stress and non-stress conditions. Arxiv - Time Series Classification via TDA
3. Machine Learning with Imbalanced Data and Data Augmentation Techniques⌗
Data Augmentation for Enhanced Performance: Use data augmentation techniques to improve the training. Imbalanced Data Analysis
4. Training with GAN Networks⌗
Anomaly Detection: Detecting the Unseen: Anomaly Detection with GANs
5. Basic Lightweight Transformers for Sentiment Analysis⌗
Sentiment Analysis with DistilBERT: Train a lightweight transformer model to classify sentiment in social media texts. DistilBERT for Sentiment Analysis