praveenhm/machine-learning-tutorials

comprehensive introduction to the field of Machine Learning

Machine-Learning-Tutorials

Comprehensive introduction to the field of great Machine Learning

Various Categories of Jupyter Notebooks:

• Python
  • Common-import file
  • Python primer
  • Python Classes
  • Numpy Primer
  • Matplotlib primer
  • Correlation Interactive graphs

• Regression

  • Linear Regression with Univariate-1
  • Polynomial regression with dataset-2
  • Understanding the Runge phenomenon
  • univariate-2 analysis
  • univariate-3 analysis
  • dataset-4 analysis
  • dataset-5 analysis
  • Power Transformations
  • Pipeline
  • Nonlinear regression
  • Old Faithful Geyser-real data
  • Multivariate regression on the Auto dataset -real data
  • Califonia housing
  • Murunga Leaves Project
  • Diamond dataset

• classification

  • Classifier-01
  • Classifier-02
  • Classifier-03
  • Nightingale
  • Wisconsin breast cancer with logistic classifier
  • Wine source

• clustering

  • Commons-imports-DBscan
  • DBSCAN sensitivity to hyperparameters
  • Old Faithful Geyser DBSCAN
  • Old Faithful Geyser k-means
  • blobs using DBSCAN
  • blobs using k-means
  • Smiley using DBSCAN
  • Smiley using k-means

• Dimensionality.reduction

• Ensemble

• Others

  • Variance R2
  • Gradient Descent
  • Tidy Data

35: Wine source classificationFile

36: Decision Tree, Random Forest and Support Vector MachinesFolder The California housing dataset modeled with decision tree, random-forest and support-vector machine

37: Density EstimatorsFile