E-learning course for Collegium da Vinci University: Machine learning – how to use the potential of data to get better results and make smart decisions

3 January 2024 lectures Rzaru
  1. Definition and applications of machine learning
    • Data deluge and the definition of machine learning
    • Machine learning examples and related fields of knowledge
    • Types of machine learning
  2. Machine learning tools used in the course
    • Programs used in the course
    • Orange Data Mining
    • Jupyter Lab
  3. Supervised machine learning
    • Machine learning process
    • Data collection, labeling and analysis
    • Feature engineering and division into training and testing sets
    • Model training and evaluation
    • Model export, corrective actions
    • Regression example
    • Classification example
    • K-nearest neighbors
    • Support vector machine method
    • Decision trees and random forests
    • Linear regression – learning process
    • Logistic regression
  4. Unsupervised machine learning
    • K-means
    • Principal component analysis
  5. Reinforcement learning
    • Examples of reinforcement learning
  6. Forecasting
    • Forecasting definition
    • Time series processing example
  7. Natural language processing
    • Natural language definition
    • Example of text normalization and tokenization
    • Text classification example
  8. Text data analysis
    • Recognizing named entities
    • Marking parts of speech and parts of a sentence
    • Detecting relationships between words
    • Sentiment analysis
    • Topic modeling
  9. Artificial neural networks
    • Definition of artificial neural networks
    • An example of a shallow neural network
    • How machines learn – gradient descent
  10. Large text models
    • Large text models, transformers
    • Prompt engineering
    • Example of generating and translating texts
  11. Computer vision
    • The field of computer vision
    • Face recognition – example
    • Autonomous vehicle
    • Example of training an autonomous vehicle
  12. Audio analysis
    • Analysis of sound signals
    • Audio recognition example
    • Speech recognition example
  13. Cloud solutions in machine learning
    • The use of cloud solutions in machine learning
    • Examples of cloud solutions in machine learning