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Disclaimer: Basic Python and Mathematics is a pre-requisite.


Machine Learning

Machine Learning is all about writing model that enables machines to learn from data, using mathematics (statistics, linear algebra, probability and calculus) and a programming language.


We will write python codes in jupyter notebook that makes it easy to visualize and explain. Download and Install: Anaconda.

I will try and explain things as we implement it.


INDEX

  • Linear Regression (code) (dataset)

  • Logistic Regression (code) (dataset)
    Logistic Regression (using Library) (code) (dataset)

  • Neural Network (code)
    Neural Network (TensorFlow) (code)
    Deep Neural Network [Binary Classification] (Keras) (code)
    Deep Neural Network [Multi-class Classification] (Keras) (code)
    Convolution Neural Network (Keras) (code)

  • Unsupervised Learning (K-Means Clustering) (code)
    Unsupervised Learning (DBSCAN Clustering) (code)

  • Support Vector Machine (Classification and Regression) (code)

  • Principal Component Analysis (code)

  • Anomaly Detection (code)

On a final note, let me know if you desire modification / found bug / have doubts at chettri@live.com.