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!