In the first course of this specialization, we will recap what was covered in the Machine Learning with TensorFlow on Google Cloud Platform Specialization (https://www.coursera.org/specializations/machine-learning-tensorflow-gcp).
Informações sobre o curso
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
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Principais avaliações do END-TO-END MACHINE LEARNING WITH TENSORFLOW ON GOOGLE CLOUD
This is a great start for advanced ml on gcp. The course labs require that you code the TODO parts, and therefore helps you gain the required coding knowledge.
The course content is rich and easy to understand. The instructors are also awesome and the quick labs are very helpful to understand the concepts in the practical world.
awesome learning experience fro the teacher from google. thanks to coursera and google for providing me such a good lesson which will be beneficial for my upcoming future and research work
Definitely adds a unique perspective on thinking about machine learning systems at scale. This course is suitable for Data Scientists, Data Engineers and Machine Learning Engineers.
Sobre Programa de cursos integrados 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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