MACHINE LEARNING

  1. What is Machine Learning?
  2. Types of Algorithms
    • Supervised Learning
      • Regression Algorithms
        • Linear Regression
        • Ridge Regression
        • Lasso Regression
        • Support Vector Regression (SVR)
      • Classification Algorithms
        • Logistic Regression
        • Decision Trees
        • Random Forest
        • Support Vector Machines (SVM)
        • k-Nearest Neighbors (k-NN)
        • Naive Bayes
        • Neural Networks
    • Unsupervised Learning
      • Clustering Algorithms
        • K-Means
        • Hierarchical Clustering
        • DBSCAN (Density-Based Spatial Clustering of Applications with Noise)
      • Association Algorithms
        • Apriori
        • Eclat
      • Dimensionality Reduction Algorithms
        • Principal Component Analysis (PCA)
        • t-Distributed Stochastic Neighbor Embedding (t-SNE)
    • Reinforcement Learning
    • Semi-Supervised Learning
    • Self-Supervised Learning
    • Ensemble Learning
  3. Dimensionality Reduction
  4. Deep Learning
    • Overview
    • Deep Learning for Natural Language Processing (NLP)
    • Neural Networks
    • Backpropagation
    • Recurrent Neural Networks (RNN)
    • Convolutional Neural Networks (CNN)
    • Long Short Term Memory Network (LSTM)
  5. Natural Language Processing
    • Overview
    • Text Classification
    • Text Preprocessing
    • Basic NLP Tasks

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