Hack Detection with Autoencoders
Detecting network hacking through unsupervised learning with Autoencoders and Scaled Exponential Linear Units (SELUs).
K-Fold Cross-Validation Algorithm Optimization
Pairing K-Fold Cross-Validation and Grid Search to simultaneously derive hyperparemeter optimization for various classification algorithms used in spam detection.
Multilabel Ensemble
Constructing an ensemble of machine learning models to enhance performance in multilabel classification.
Active vs Passive Learning
Evaluating relative performance gains in a model employing active learning to detect false bank notes.
Supervised, Semi-Supervised and Unsupervised Learning
Comparing performance of different machine learning approaches for brest cancer detection.
Multi-Class Multi-Label Classification
Categorizing frog Families, Genus and Species from Mel Frequency Cepstrum Coefficients (MFFC) audio recordings.
Machine Learning Engineering
Implementing a deployment-ready object-oriented machine learning model and assessing its robustness with unit testing.
Time Series Classification
Applying feature engineering techniques along with machine learning models to classify time series data.
Time Series Forecasting
Forecasting future sales with multiple statistical, machine leaning and artificial intelligence models.
Manually Coded Multilayer Perceptron
Manually developed multilayer perceptron - a basic MLP "coded by hand".
AutoML with H20
Developing a weather forecasting system through automated machine learning (AutoML) tools and lagging time features.