Concepts

By: Brian Msane

• Regression
• Generalization and Estimation
• Statistics (Correlation, Hypothesis testing, Distributions)
• Classification
• Neural networks, backpropagation
• Machine learning algorithms
• Deep Learning algorithms
• Exploratory Data Analysis and Visualizations
• Federated learning
• Time series modeling
• Reinforcement learning
• Natural Language Processing
• Computer Vision
• Recommendation engines
• Hyper-parameter tuning
• Transformer models
• Transfer learning
• Explainable AI

Machine Learning Models

• Linear Regression
• Logistic Regression
• Decision Tree
• Random Forest
• Support Vector Machines
• k-Nearest Neighbours
• Naive Bayes
• Gradient Boosting Machines
• Adaptive Boosting
• XGBoost
• LightGBM
• CatBoost
• Ridge Regression
• Lasso Regression
• k-Means Clustering
• Hierarchical Clustering
• DBSCAN (Density-Based Spatial Clustering)
• Principal Component Analysis and Independent Component Analyis

Deep Learning Models

• Discriminative
  • Multi Layer Perceptron
  • Convolutional Neural Networks
  • Recurrent Neural Networks
    • Long-Short Term Memory
    • Bidirectional-LSTM
    • Gated Recurrent Units
• Generative
  • Generative Adversarial Networks
  • Auto Encoder
    • Sparse AE
    • Denoising AE
    • Contractive AE
    • Variational AE
  • Self-Organizing Map
  • Restricted Boltzman Machines
  • Deep Belief Network