Build, train, and evaluate machine learning models using TensorFlow and its high-level Keras API. This course provides practical guidance on TensorFlow's core components, data handling, model construction, and deployment preparation, assuming foundational knowledge of machine learning principles.
Prerequisites ML foundations and Python
Level:
TensorFlow Core Operations
Manipulate tensors, perform mathematical operations, and understand automatic differentiation.
Keras API Model Building
Construct models using the Sequential and Functional APIs in Keras.
Model Training and Evaluation
Compile models with appropriate optimizers and loss functions, train them using fit(), and evaluate performance.
Data Input Pipelines
Create efficient data loading pipelines using the tf.data API.
Model Persistence
Save and load trained TensorFlow models and weights.
TensorBoard Integration
Utilize TensorBoard for visualizing training metrics and model graphs.