Design and building of TensorFlow input data pipelines, creating ML models using TensorFlow and Keras, strategies to improve ML model accuracy, and methods to scale and specialize ML models. This would cover practical aspects of TensorFlow in Google Cloud environment, focusing on model training and optimization for real-world applications. Understanding how to use features in ML models for improve
Mar 2, 6:30 – 8:00 PM
AICertification PrepCertification Study GroupCloudCloud HeroCloud Study JamMachine LearningRoad to Google Developers CertificationTensorFlow
About this event
What We Will Discuss:
Reviewing progress in the machine learning certification journey
𝗦𝗽𝗲𝗰𝗶𝗮𝗹 𝗔𝗱𝗱𝗶𝘁𝗶𝗼𝗻 - Lightening talk by Adam Berg
Content Review by Vasudev Maduri
Data Preparation and Processing
Solution Architecture with TensorFlow Extended (TFX)
Data Ingestion Challenges and Solutions
Sample Question Review
Previewing next steps and topics, including course completions and material reviews.
How to prepare for this session?
To enhance your certification journey, we recommend completing the MLE Learning Path courses on Google Cloud Skills Boost