00:00/00:00
Lecture 14 of 21
Applying-Gradient-Descent
Course Content
0 / 21 completedSection 1: Course Curriculum21 videos
Introduction
37m
Refund-Request-Filtering
1h 30m
Creating-the-Data-Converter
1h 30m
Applying-the-Data-Converter
1h 30m
Challenges-in-Creating-a-Production-Model
1h 30m
Boundaries-in-a-Decision-Model
1h 30m
Neural-Network-Data
1h 30m
Validating-Pixel-Data-Neural-Network
1h 30m
Inferring-Using-the-Pixel-Data-Model
1h 30m
Training-a-Pixel-Data-Model
1h 30m
Improve-Accuracy-of-Model
1h 12m
Learning-Multipliers-with-Larger-Sample
1h 30m
Applying-All-Weight-Changes
1h 6m
Applying-Gradient-Descent
1h 26mNow Playing
Sigmoid-Function
1h 30m
Validating-Weight-Accuracy
1h 30m
Preprocessing-Sample-Data
52m
Combining-Models
36m
Extending-the-Principles-of-Machine-Learning
1h 5m
Developing-a-Production-Model
1h 30m
Wrapping-Up
1h 18m