Day 1 - TensorFlow Mechanics

  • Terminology, components, creating and executing the graph
  • Get to know and sanitize your data
  • Create visualizations

Day 1 - Regression

  • Model: Predict Housing Prices
  • Identify features like square footage, number of bedrooms and bathrooms and use them to predict the price.
  • Regression is used everywhere. I'm sure your company has a regression problem that needs solving!

Day 2 - Classification

  • Model: Analyzing Sentiment. Is this review positive or negative?
  • Model: Image Classification. What number does this image look like?
  • Learn how problems can be re-framed to be Regression or Classification

Day 3 - Clustering and Retrieval

  • Model: Finding Similar Documents
  • Automatically create classes from your data similar to each other
  • Retrieve similar documents

Day 4 - Recommendation

  • Model: Recommend Videos Based on History
  • Learn uses of recommendation engines
  • Learn how recommendations are different than finding similar items

Day 5 - Serving and Fun!

  • Now that you have a few models, how do you serve them?
  • Exporting, Versioning, Testing
  • Skills needed to keep your machine learning service running
  • Fun with Deep Neural Networks!