TensorFlow on Google Cloud - Locales
Offered By: Google via Google Cloud Skills Boost
Course Description
Overview
This course, TensorFlow on Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in TensorFlow on Google Cloud. This course covers designing and building a TensorFlow 2.x input data pipeline, building ML models with TensorFlow 2.x and Keras, improving the accuracy of ML models, writing ML models for scaled use and writing specialized ML models.
Syllabus
- Introduction to the Course
- Introduction
- Introduction to the TensorFlow ecosystem
- Introduction to the TensorFlow ecosystem
- Introduction to Tensorflow
- TensorFlow API hierarchy
- Components of Tensorflow: Tensors and variables
- Quiz: Introduction to the TensorFlow Ecosystem
- Design and Build an Input Data Pipeline
- Introduction
- An ML recap
- Training on large datasets with tf.data API
- Working in-memory and with files
- Getting the data ready for model training
- Embeddings
- Lab intro: TensorFlow Dataset API
- TensorFlow Dataset API
- Scaling data processing with tf.data and Keras preprocessing layers
- Lab intro: Classifying structured data using Keras preprocessing layers
- Classifying Structured Data using Keras Preprocessing Layers
- Quiz: Design and Build Input Data Pipeline
- Building Neural Networks with the TensorFlow and Keras API
- Introduction
- Activation functions
- Training neural networks with TensorFlow 2 and the Keras Sequential API
- Serving models in the cloud
- Lab intro: Introducing the Keras Sequential API on Vertex AI Platform
- Introducing the Keras Sequential API on Vertex AI Platform
- Training neural networks with TensorFlow 2 and the Keras Functional API
- Lab intro: Build a DNN using the Keras Functional API on Vertex AI Platform
- Build a DNN using the Keras Functional API
- Model subclassing
- (Optional) Lab intro: Making new layers and models via subclassing
- (Optional) Making New Layers and Models via Subclassing
- Regularization basics
- How can we meaure model complexity: L1 vs. L2 Regularization
- Quiz: Building Neural Networks in TensorFlow with Keras API
- Training at Scale with Vertex AI
- Introduction
- Training at scale with Vertex AI
- Lab intro: Training at scale with the Vertex AI Training Service
- Training at Scale with Vertex AI Training Service
- Quiz: Training at Scale with Vertex AI
- Summary
- Summary
- Resource: All quiz questions
- Resource: All readings
Tags
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