Machine Learning with Scikit-Learn Training

Live Online & Classroom Enterprise Training

Master the most efficient Python library and improve your algorithms' performance with our Scikit-Learn course. Gain hands-on expertise on the built-in tools for all standard machine learning tasks.

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Key Features
  • Lifetime Access

  • CloudLabs

  • 24x7 Support

  • Real-time code analysis and feedback

  • 100% Money Back Guarantee

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What is Machine Learning with Scikit-Learn Course about?

Master the core concepts of statistical learnings implemented in Scikit-learn to quickly extract features from any type of data. In a practice-as-you-learn approach, gain in-depth working knowledge of tools in Scikit learn library to implement classification, regression, clustering, dimensionality reduction and many more classic data science concepts.

In cloud labs, practice preprocessing of data, model selection, classical regression, naive Bayes, SVM and much more.

Be industry-ready to develop cutting-edge intelligent apps in the fastest possible time with our machine learning models with Scikit-Learn training course.

Suggested Audiences

Expert developers adding machine learning and database methods to apps


What are the objectives of Machine Learning with Scikit-Learn Course ?

This Machine Learning with Scikit-Learn course enables you to:

  • Install, configure and test Scikit-learn library to work with Python in Linux / Windows
  • Gain a deep understanding of built-in Machine Learning models and usage
  • Implement image recognition using SVM
  • Classify text using Naive Bayes \
  • Deploy a decision tree classifier Implement unsupervised learning with PCA
  • Master advanced features such as feature extraction, feature selection, and model selection.
  • Lead smart-app development projects that manipulate complex and large datasets


Available Training Modes

Live Online Training

12 Hours

Classroom Training


2 Days

Who is Machine Learning with Scikit-Learn Course for?

  • Anyone who wants to add Machine Learning with Scikit-Learn skills to their profile
  • Teams getting started on Machine Learning with Scikit-Learn projects
  • What are the prerequisites for Machine Learning with Scikit-Learn Course?

    Required: Development experience in Python, Linux, Hands-on with Python libraries, Fair understanding of Machine Learning, Deep Learning Models

    Suggested: NA

    Course Outline

    • Installing Scikit
      • Linux
      • Windows
      • Checking Installation
    • Machine Learning with Scikit-learn
      • Learning Models
      • Supervised Learning
      • Unsupervised Learning
    • ----------Supervised Learning----------
    • Support Vector Machines
      • Image Recognition
      • Training Support Vector Machines
    • Naive Bayes
      • Text Classification
      • Preprocessing data
      • Training the classifier
      • Evaluating the performance
    • Decision Trees
      • Preprocessing the data
      • Training a decision tree classifier
      • Interpreting the decision tree
      • Evaluating the performance
    • ----------Unsupervised Learning----------
    • Principal Component Analysis
      • Visualization
      • Feature Selection
    • Clustering handwritten digits with k-means
      • Alternative Clustering Methods
    • Advanced Features
      • Feature extraction
      • Feature selection
      • Model selection

    Who is the instructor for this training?

    The trainer for this Machine Learning with Scikit-Learn Training has extensive experience in this domain, including years of experience training & mentoring professionals.