E-Books →TensorFlow 2 Pocket Reference Building and Deploying Machine Learning Models

When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the training process? How do you leverage a pretrained model using transfer learning? How do you perform hyperparameter tuning? Pick up this pocket reference and reduce the time you spend searching through options for your TensorFlow use cases.Understand best practices in TensorFlow model patterns and ML workflowsUse code snippets as templates in building TensorFlow models and workflowsSave development time by integrating prebuilt models in TensorFlow HubMake informed design choices about data ingestion, training paradigms, model saving, and inferencingAddress common scenarios such as model design style, data ingestion workflow, model training, and tuning