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In this course, you will :
- Learn how to define constants and variables, add and multiply tensors, and compute derivatives. Knowledge of linear algebra is advantageous but not required.
- Learn how to use TensorFlow 2 to build, solve, and predict models.
- TensorFlow model construction 2. In this chapter, you'll use the same tools to build, train, and predict neural networks. To reduce overfitting, you will learn how to define dense layers, use activation functions, choose an optimizer, and use regularisation.
- Discover how to use the Estimators API to speed up the model definition and training process while avoiding errors.
Syllabus :
- Introduction to TensorFlow
- Linear models
- Neural Networks
- High Level APIs
