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Jhean Steffan Martines de Camargo

Member since 2021

Diamond League

9655 points
Production Machine Learning Systems Earned فبراير 16, 2024 EST
Build, Train and Deploy ML Models with Keras on Google Cloud Earned فبراير 11, 2024 EST
Planetary Scale Earth Observation with Google Earth Engine Earned يناير 29, 2024 EST
DEPRECATED BigQuery Basics for Data Analysts Earned يناير 19, 2024 EST
Introduction to Generative AI Earned يناير 17, 2024 EST
Conversational AI on Vertex AI and Dialogflow CX Earned يناير 16, 2024 EST

This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.

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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.

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Learn how public sector agencies and academic researchers leverage Google Earth Engine to distill meaningful insights from petabytes of Earth Observation at planetary scale. Google Earth Engine is a fully managed geospatial platform that has enabled research for more than a decade in environmental areas such as forestry, agriculture, water, and sustainability.

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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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In this course you will learn how to use the new generative AI features in Dialogflow CX to create virtual agents that can have more natural and engaging conversations with customers. Discover how to deploy generative fallback responses to gracefully handle errors and omissions in customer conversations, deploy generators to increase intent coverage, and structure, ingest, and manage data in a data store. And explore how to deploy and maintain generative AI agents using your data, and deploy and maintain hybrid agents in combination with existing intent-based design paradigms.

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