Course Outline
Introduction
- TensorFlow 2.x vs previous versions -- Key enhancements
Configuring TensorFlow 2.x
Exploring TensorFlow 2.x Features and Architecture
Mechanics of Neural Networks
Developing Deep Learning Models with TensorFlow 2.x
Data Analysis
Data Preprocessing
Model Construction
Developing an Advanced Image Classifier
Model Training
Training Performance: GPU vs TPU
Model Evaluation
Generating Predictions
Assessing Prediction Accuracy
Model Debugging
Model Persistence
Cloud Deployment
Mobile Device Deployment
Embedded System (IoT) Deployment
Cross-Language Model Integration
Troubleshooting Strategies
Wrap-up and Conclusion
Requirements
- Familiarity with Python programming.
- Proficiency with the Linux command line.
Target Audience
- Software Developers
- Data Scientists
Testimonials (4)
The training was organized and well-planned out, and I come out of it with systematized knowledge and a good look at topics we looked at
Magdalena - Samsung Electronics Polska Sp. z o.o.
Course - Deep Learning with TensorFlow 2
Trainer's knowledge and the fact they were very approachable. They could easily convey important knowledge
Mateusz Stachyra - Samsung Electronics Polska Sp. z o.o.
Course - Deep Learning with TensorFlow 2
I liked that we covered the basics too
Tomasz - Samsung Electronics Polska Sp. z o.o.
Course - Deep Learning with TensorFlow 2
The trainer explained the content well and was engaging throughout. He stopped to ask questions and let us come to our own solutions in some practical sessions. He also tailored the course well for our needs.
