Custom Prediction Routine on Google AI Platform

via Coursera

Coursera

1275 Courses


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Overview

Unlock the power of AI with our comprehensive course on deploying custom prediction routines on Google AI Platform. Ideal for individuals with a Google Cloud Platform (GCP) account, this project-based course spans over 2 hours, guiding you through the nuances of leveraging AI Platform's capabilities beyond conventional TensorFlow models. Before diving in, ensure that you're proficient in Python, familiar with GCP, and have the Custom Prediction Routine feature activated on your account. This course, available on Coursera's interactive Rhyme platform, offers a hands-on learning experience directly in your browser, eliminating the need for additional setup.

Discover the flexibility of using custom prediction routines, allowing the use of non-TensorFlow models such as Keras h5 files without conversion. This course emphasizes practical skills, including working with image data, encoding, and decoding techniques for effective data transmission. By the end of this journey, deploying and using models on Google's AI Platform will become second nature. Participants will gain instant access to a cloud desktop equipped with essential tools like Python, Jupyter, and TensorFlow, specifically configured for this project. Although designed primarily for learners in North America, efforts are underway to extend this enriching learning experience to other regions. Enroll in this course to explore the realms of Artificial Intelligence and Machine Learning on Coursera.

Categories include Artificial Intelligence Courses and Machine Learning Courses, ensuring a comprehensive learning pathway. Please note, participating in this course involves usage charges by GCP according to your account's tariff. Join us on Coursera and advance your skills in deploying custom prediction routines on the Google AI Platform.

Syllabus


Taught by

Amit Yadav


Tags

provider Coursera

Coursera

1275 Courses


Coursera

pricing Paid Course
language English
duration 1-2 hours
sessions On-Demand
level Intermediate