- What is TensorFlow.js
- TensorFlow features
- Math operations and memory management
Preparing the Development Environment
- Installing and configuring TensorFlow.js
- Running TensorFlow.js on a browser
- Running TensorFlow.js under Node.js
- Reading and writing to data
- Preparing features
- Labeling data
- Normalizing data
- Splitting data into test data and training data
Machine Learning Models
- Creating a model
- Creating layers
- Compiling a model
Training and Testing
- Training models
- Testing models
Predictions and Regressions
- Integrating a UI
- Loading a model
- Visualizing predictions
- Creating regressions
- Working with binary classification
- Working with multi-class classification
Summary and Conclusion
- Data Scientists
I started with close to zero knowledge, and by the end I was able to build and train my own networks.
Huawei Technologies Duesseldorf GmbH
Very updated approach or api (tensorflow, kera, tflearn) to do machine learning
Usama Adam - TWPI
The way he present everything with examples and training was so useful
Ibrahim Mohammedameen - TWPI
Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject
Ali Kattan - TWPI
Topic selection. Style of training. Practice orientation
Given outlook of the technology: what technology/process might become more important in the future; see, what the technology can be used for
I liked the opportunities to ask questions and get more in depth explanations of the theory.
Very good all round overview.Good background into why Tensorflow operates as it does.
I was amazed at the standard of this class - I would say that it was university standard.
I really appreciated the crystal clear answers of Chris to our questions.
About face area.
Tomasz really know the information well and the course was well paced.
Raju Krishnamurthy - Google
Trainer was very knowledgeable and open to questions, liked to draw diagrams and explained things in a pretty good way