AnwarAsif / MLEssentials

Machine Learning Essentials

MLEssentials

Machine Learning Essentials

Terminologies

1. Pipelines: A sequence of data processing components is called data pipeline.

ML Algorithms

1. Regressions

• Linear Regression
• Tree Regression
• Forest Regression

9. Unsupervised Learning Techniques

• Use case: Unsupervised Learning is useful for Clustering, Anomaly dettecton and Density estimation
  • Clustering: group similar instances together into clusters
    • Data Analysis
    • Customer Segmentation
    • Recommender system
    • search engines
    • image classification
    • semi-supervised learning
    • dimensionality reduction
  • Anomaly Detection: what normal data looks like then use that to detect abnormal instances.
    • new trend in time serise
    • find defective items
  • Desnsity Estimation: Estimating the probability density function PDF of the random process
    • anomaly detecttion: instances located in the very low-density regions liekly to be anamalies
    • analysis and visualization