Python and Machine Learning

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Python is a popular open source language. It has libraries for almost everything, including web programming, administrative tasks, system programming, mathematics, machine learning, and graphics.
This course is intended for data scientists and software engineers. It gives them practical level of experience, achieved through a combination of about 50% lecture, 50% lab work

Before taking this course, students should be able to navigate Linux command line, and have familiarity with programming

5 Days/Lecture & Lab

This course is designed for Data Scientists, Developers, and Administrators.

  • Python Introduction
  • Python Language Overview and First Steps
  • Python OOP
  • Pandas
  • NumPy
  • Python – DB Programming
  • Python – Web Programming
  • Visualization
  • NLTK
  • Machine Learning (ML) Overview
  • Machine Learning Environment
  • Machine Learning Concepts
  • Feature Engineering (FE)
  • Linear regression
  • Logistic Regression
  • Classification : SVM (Supervised Vector ::Machines)
  • Classification : Decision Trees & Random ::Forests
  • Classification : Naive Bayes
  • Clustering (K-Means)
  • Principal Component Analysis (PCA)
  • Recommendation (Collaborative filtering)
  • Final workshop (time permitting

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