Machine Learning with TensorFlow on Google Cloud em Português Brasileiro

How Google does Machine Learning em Português Brasileiro provides insights into using the Vertex AI platform for creating, training, and deploying AutoML models without writing code. It also covers best practices for implementing machine learning on the Google Cloud Platform, utilizing AI responsibly, and working with ML tools and environments.

Launching into Machine Learning em Português Brasileiro focuses on improving data quality, performing exploratory data analysis, creating and training AutoML models using Vertex AI and BigQuery ML, optimizing and evaluating models, and creating scalable datasets for training, evaluation, and testing.

Intro to TensorFlow em Português Brasileiro leverages the flexibility and ease of use of TensorFlow 2.x and Keras to create, train, and deploy machine learning models. It covers working with datasets, designing and creating data input pipelines, and practical experience with loading various types of data. The module also delves into creating deep learning models using Keras Sequential and Keras Functional APIs, and training, deploying, and scaling ML models using the Cloud AI Platform.

Feature Engineering em Português Brasileiro explores the use of Feature Store in Vertex AI, migration of raw data to attributes, attribute engineering, attribute pre-processing using Apache Beam and Cloud DataFlow, and utilizing tf.Transform.

Art and Science of Machine Learning em Português Brasileiro focuses on essential intuition, common ML model optimization techniques, generalizing models using regularization techniques, understanding the effects of hyperparameters, and specifying optimization methods in TensorFlow code.