Course
Skills
The Art and Science of ML
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
3mins
The Art of ML
29mins
- The Art of ML 0m
- Introduction 2m
- Regularization 5m
- L1 & L2 Regularizations 5m
- Lab Intro - Regularization 0m
- Lab Solution - Regularization 3m
- Learning Rate and Batch Size 5m
- Optimization 1m
- Practicing with Tensorflow Code 1m
- Lab Intro - Hand-Tuning ML Models 0m
- Lab: Improve model accuracy by hand-tuning hyperparameters 0m
- Lab Solution - Hand-Tuning ML Models 7m
Hyperparameter Tuning
7mins
- Hyperparameter Tuning 0m
- Introduction 1m
- Parameters vs Hyperparameters 2m
- Think Beyond Grid Search 3m
- Lab Intro - Improve Model Accuracy by Hyperparameter Tuning with Cloud MLE 0m
- Lab: Improve model accuracy by hyperparameter tuning with AI Platform 0m
- Lab Solution - Improve Model Accuracy by Hyperparameter Tuning with Cloud MLE 1m
A Pinch of Science
27mins
The Science of Neural Networks
71mins
Embeddings
30mins
Custom Estimator
31mins
Summary
5mins
