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: Deep Learning using Tensorflow and Keras

Lab: Deep Learning using Tensorflow and Keras

Objectives

  • Create neural networks for deep learning using Tensorflow and Keras

Introducing Tensorflow and Keras

  • Vast API. Pick any use-case. Full list here https://keras.io/examples/

  • TODO: Add more use-cases from design doc

  • Suggestion - simple image recognition

    • https://www.kaggle.com/learn/intro-to-deep-learning

    • https://www.kaggle.com/learn/computer-vision

Lab: Predictive Data Analysis using Scikit-Learn Lab: Deep Learning using PyTorch
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