Book Content
chapters • 10h44m total length
1. Effective Planning of Deep Learning-Driven Projects
2. Data Preparation for Deep Learning Projects
3. Developing a Powerful Deep Learning Model
4. Experiment Tracking, Model Management, and Dataset Versioning
5. Data Preparation in the Cloud
6. Efficient Model Training
7. Revealing the Secret of Deep Learning Models
8. Simplifying Deep Learning Model Deployment
9. Scaling a Deep Learning Pipeline
10. Improving Inference Efficiency
11. Deep Learning on Mobile Devices
12. Monitoring Deep Learning Endpoints in Production
13. Reviewing the Completed Deep Learning Project
