Learn about the Speech Analysis Framework used to transcribe audio, create a data pipeline workflow for analytics, and then visually represent the data.
Use AI Platform on Google Cloud and predict customer lifetime value (CLV).
Learn how to analyze and evaluate the quality of the training phrases supplied to your Dialogflow agent’s intents.
An overview of approximate similarity with an end-to-end example for performing real-time text semantic search.
An overview to start building, securing, and scaling a chatbot using your own data with Dialogflow Enterprise Edition on Google Cloud.
Learn how to automate receiving, measuring, and tailoring creative insights with Google Cloud’s machine learning and data warehousing capabilities.
Run an inference at large scale on NVIDIA TensorRT 5 and T4 by setting up a multi-zone cluster with an autoscaling group based on GPU utilization.
Explore common architectures on Google Cloud Platform for ML model predictions, as well as techniques for minimizing the latency of ML systems.
Learn how prepare the data, train the models, and what the code is and how it’s used.
Deploy models to a production system.
An overview guidance on how to implement a recommendation system with TensorFlow and AI Platform including outlining theory, and describing WALS algorithm.
Implement a ML system with TensorFlow and AI Platform and install TensorFlow model code on a development system and run the model on the MovieLens dataset.
Learn how to train the recommendation system and tune hyperparameters using AI Platform in Google Cloud.
Apply TensorFlow model to data from Google Analytics 360 to produce content recommendations for a website.
Deploy a production system on Google Cloud to serve recommendations and perform periodic updates to the recommendation model.
Explore how to use the Vision API and AutoML Vision to power your image search and classification application.
Describes and compares the different design approaches for calling a machine learning model during a Dataflow pipeline.