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Advanced Machine Learning on Google Cloud

This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs. This specialization picks up where “Machine Learning on GCP” left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text. It ends with a course on building recommendation systems. Topics introduced in earlier courses are referenced in later courses, so it is recommended that you take the courses in exactly this order.

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What's inside

Four courses

Natural Language Processing on Google Cloud

This course introduces Google Cloud's NLP products and solutions. It also explores the processes, techniques, and tools for developing NLP projects with neural networks using Vertex AI and TensorFlow. By the end, you'll be able to:

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Production Machine Learning Systems

(0 hours)

In this course, we explore the components and best practices for building high-performing ML systems in production environments. We cover considerations such as static and dynamic training and inference, distributed TensorFlow, and TPUs. This course focuses on the characteristics of effective ML systems beyond their predictive capabilities.

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Recommendation Systems on Google Cloud

(0 hours)

In this course, you'll apply your knowledge of classification models and embeddings to build a machine learning pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.

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Computer Vision Fundamentals with Google Cloud

(0 hours)

This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models, or convolutional neural network (CNN) models.

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Time

1 hours

Via

Coursera

Institution

Google Cloud

Instructor

Google Cloud Training

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