Machine Learning Algorithms

Module 1: Supervised Learning

Lesson 1: Regression

  • Linear Regression
  • Polynomial Regression
  • Evaluation Metrics

Lesson 2: Classification

  • Logistic Regression
  • Decision Trees
  • Support Vector Machines (SVM)

Module 2: Unsupervised Learning

Lesson 1: Clustering

  • K-means Clustering
  • Hierarchical Clustering
  • Cluster Evaluation

Lesson 2: Dimensionality Reduction

  • Principal Component Analysis (PCA)
  • t-SNE
  • Applications in Data Visualization

Module 3: Advanced Topics in Machine Learning

Lesson 1: Neural Networks

  • Introduction to Neural Networks
  • Deep Learning with TensorFlow/Keras
  • Convolutional Neural Networks (CNNs)

Lesson 2: Natural Language Processing (NLP)

  • Text Processing
  • Sentiment Analysis
  • Named Entity Recognition (NER)