neural networks

  • Dimensionality Reduction

    • Main Approaches for Dimensionality Reduction

    • Principal Component Analysis

  • Introduction to Artificial Neural Networks

    • The Perceptron

    • Multi-layer Perceptron (MLP) and Backpropagation

    • Training an MLP

    • Training a Deep Neural Network (DNN)

    • Fine-tuning Neural Network Hyperparameters

  • Convolution Neural Networks (CNN)

    • Convolution Layer

    • Pooling Layer

    • CNN Architectures

  • Recurrent Neural Networks (RNN)

    • Recurrent Neurons

    • Training RNNs

    • Deep RNNs

  • Classification

    • Training a Binary Classifier

    • Performance Measures

    • Multiclass Classification

    • Error Analysis

    • Multilabel Classification

    • Multioutput Classification

  • Training Models

    • Linear Regression

    • Gradient Descent

    • Polynomial Regression

    • Learning Curves

    • Regularized Linear Models

    • Logistic Regression

  • Support Vector Machines

    • Linear SVM Classification

    • Non-linear SVM Classification

    • SVM Regression

    • Under the Hood