Red Hat Red Hat OpenShift Data Science
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Red Hat OpenShift Data Science

    • Welcome
    • Classroom Environment
    • Chapter 1: Introduction
      • Introduction to RedHat OpenShift Data Science
      • Jupyter Notebooks
      • Lab: Jupyter Notebooks
    • Chapter 2: Data Analysis and Visualization
      • Data Analysis and Visualization
      • Lab: Explore Data with Pandas
      • Lab: Multi-dimensional data analysis with NumPy
      • Lab: Visualizing Data with Matplotlib
    • Chapter 3: Machine Learning
      • Machine Learning and Deep Learning
      • Lab: Predictive Data Analysis using Scikit-Learn
      • Lab: Deep Learning using Tensorflow and Keras
      • Lab: Deep Learning using PyTorch
    • Chapter 4: Deploying and Serving Machine Learning Models
      • Serving Machine Learning models
      • Lab: Serving Machine Learning models using Flask
      • Lab: Streaming Data with RedHat OpenShift Streams for Kafka
Red Hat OpenShift Data Science 1.25
  • Red Hat OpenShift Data Science
    • 1.25
  • Red Hat OpenShift Data Science
  • Chapter 3: Machine Learning
  • Lab: Predictive Data Analysis using Scikit-Learn

Lab: Predictive Data Analysis using Scikit-Learn

Objectives

  • Create predictive machine learning models using Scikit-Learn

Introducing Scikit-Learn

  • Image and Object classification - https://scikit-learn.org/stable/auto_examples/classification/plot_digits_classification.html#sphx-glr-auto-examples-classification-plot-digits-classification-py

  • TODO: Add more use-cases from Red Hat internal resources

Machine Learning and Deep Learning Lab: Deep Learning using Tensorflow and Keras
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