AI and ML projects and applications developed to learn various implementations
A machine learning journey in predicting battery cycle life for mission critical applications (takes 1 minute to open) 
Goal: Predicting Modern Battery Lifetime using Machine Learning using a Stanford-Toyota Research Dataset (open)
- quantitative and and classification forecasting exploration
- statistical data analysis (One-Way ANOVA, ANOVA Ordinary Least Squares, and the Shapiro-Wilk, Levene, Turnkey tests)
- feature discovery (naive and physics-informed approaches)
- Multivariate Regression Model Implementations (naive, physics-informed)
- Hyperparameter Optimisation (LASSO, elastic net)
- Multivariate Classifier Model
Autoregressive integrated moving average (ARIMA) and Bayes Linear Regression Models (solar power forecast)
Goal: Forecasting solar power generation from weather data
Restricted Boltzman Machine (Convolutional Neural Network for Computer Vision) PDF-preview of livescript
Goal: Labelling Street View House Numbers (SVHN dataset). Associated files are under RBM-files
Goal: estimating the Friedman-Silverman function of the 10-dimension unit hypercube
Goal: build and evaluate several models to estimate fuel consumption as a function of car acceleration and weight.
... more to come semper discens