Machine-Learning

Collection of Machine Learning algorithms implemented in Matlab/Python:

• General concepts

  • Lagrangian
  • Gaussian Processes
  • Gradient Descent
  • Constrained Optimization
  • Singular Value Decomposition [view]

• Dimensionality Reduction

  • PCA (Project: EigenFaces using the YaleFace Database)
  • Auto-encoder

• Classification

  • Linear Features
  • Polynomial Features
  • Naive Bayes [view]

• Regression

  • Linear
  • Polynomial

• Clustering

  • K-Means (Customer Segmentation, Image Compression)
  • Mixture of Gaussians (MoG)
  • DBScan

• Decision Trees [view]

• Neural Networks

  • Project: Estimating bike-sharing patterns [view]

• Auto-encoder

  • Project: Detect anomalies in Ford’s historical stock price time series data with an LSTM autoencoder [view]

• Convolutional Neural Networks (CNN)

  • Project: Dog-breed classifier [view]

• Recurrent Neural Networks (RNN)

  • Project: Character Level RNN [view]

• Long-Short Term Memory (LSTM)

  • Project: TV Script Generation [view]

• Generative Adversarial Networks (GAN)

  • Project: Human Face generation [view]

• Transfer Learning:

  • Demonstrate Transfer learning using the VGG16 Model on the CIFAR10 Dataset [view]

• Model Improvement Techniques

  • Handling imbalanced datasets using SMOTE [view]

• Other Projects

  • Segmenting Neighborhoods using ML and the FourSquare API [view]
  • MNIST Handwritten Digit Classification [view]
  • Traffic Signal Classification (CNN) [BelgiumTSC Dataset] [view]

Requirements

Python, TensorFlow, scikit-learn