Machine Learning using Python Introductory Training

Machine Learning using Python Introductory Training

Machine Learning course will give you overview of machine learning, a form of artificial intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming.

You will grasp machine learning concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modelling to develop algorithms and prepare you for the role of Machine Learning Engineer. Scikit-learn (formerly scikits.learn) is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

3 Days Workshop

Course Outline

Day 1

  • Steps 1 and 2
  • Steps 3 and 4
  • How it Works
  • Steps 5 and 6
  • Supervised Learning Model Considerations
  • Knowledge Check
  • Scikit-Learn
  • Knowledge Check

Day 2

      • Supervised Learning Models – Linear Regression
      • Supervised Learning Models – Logistic Regression
      • Unsupervised Learning Models
      • Pipeline
      • Model Persistence and Evaluation
      • Knowledge Check
      • Natural Language processing with Scikit Learn
      • NLP Overview
      • NLP Applications
      • Knowledge check

Day 3

      • NLP Libraries-Scikit
      • Extraction Considerations
      • Scikit Learn-Model Training and Grid Search
      • Assignment 01
      • Demo Assignment 01
      • Assignment 02
      • Demo Assignment 02
      • Quiz


Who should take the course?

  • Software developers
  • IT managers
  • Service management professionals
  • Technology Managers
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