Course
Skills
Feature Engineering
Want to know how you can improve the accuracy of your ML models? What about how to find which data columns make the most useful features? Welcome to Feature Engineering where we will discuss good vs bad features and how you can preprocess and transform them for optimal use in your models.
What you'll learn
Want to know how you can improve the accuracy of your ML models? What about how to find which data columns make the most useful features? Welcome to Feature Engineering where we will discuss good vs bad features and how you can preprocess and transform them for optimal use in your models.
Table of contents
Introduction to Course
1min
Raw Data to Features
40mins
- An Overview of Feature Engineering 12m
- Raw Data to Features 3m
- Good vs Bad Features 3m
- Features Known at Prediction-time 3m
- Features should be Numeric 0m
- Features Should Have Enough Examples 1m
- Bringing Human Insight 0m
- Representing Features 9m
- ML vs Statistics 3m
- Lab Intro: Basic Feature Engineering in BQML 1m
- Getting Started With GCP And Qwiklabs 4m
- Lab: Performing Basic Feature Engineering in BQML 0m
- Lab Intro: Basic Feature Engineering in Keras 1m
- Lab: Performing Basic Feature Engineering in Keras 0m
- Resources 0m
Preprocessing and feature creation
46mins
- Beam and Dataflow 10m
- Lab Intro: Simple Dataflow Pipeline 0m
- Lab: A simple Dataflow pipeline (Python) 0m
- Lab Solution: A Simple Dataflow Pipeline 7m
- Data Pipelines that Scale 6m
- Lab Intro: MapReduce in Dataflow 1m
- Lab: MapReduce in Dataflow (Python) 0m
- Lab Solution: MapReduce in Dataflow 4m
- Preprocessing with Cloud Dataprep 7m
- Lab Intro: Computing Time-Windowed Features in Cloud Dataprep 10m
- Lab: Computing Time-Windowed Features in Cloud Dataprep 0m
- Lab Solution: Computing Time-Windowed Features in Cloud Dataprep 1m
- Resources 0m
Feature Crosses
65mins
- Introducing Feature Crosses 1m
- What is a Feature Cross 6m
- Discretization 2m
- Memorization vs. Generalization 5m
- Taxi colors 5m
- Lab Intro: Feature Crosses to create a good classifier 0m
- Lab Solution: Feature Crosses to create a good classifier 6m
- Sparsity + Quiz 6m
- Lab Intro: Too Much of a Good Thing 1m
- Lab Solution: Too Much of a Good Thing 7m
- Implementing Feature Crosses 5m
- Embedding Feature Crosses 9m
- Feature Creation in TensorFlow 3m
- Feature Creation in DataFlow 3m
- Lab Intro: Improve ML Model with Feature Engineering 1m
- Lab: Improve Machine Learning model with Feature Engineering 0m
- Lab Solution (p1): ML Fairness Debrief 4m
- Lab Intro: Advanced Feature Engineering in BQML 1m
- Lab: Performing Advanced Feature Engineering in BQML 0m
- Lab Intro: Advanced Feature Engineering in Keras 0m
- Lab: Performing Advanced Feature Engineering in Keras 0m
- Resources 0m
TensorFlow Transform
23mins
Summary
7mins
Course Resources
0mins
