Generative AI enables amazing creative solutions, but must be implemented responsibly to minimize the risk of harmful content generation.

Learn the essential skills for data preparation and basic statistical analysis in retail. Understand how to clean and analyze retail data to uncover insights for better business decisions.

Learn the fundamentals of reward modeling for generative AI using Hugging Face. Discover how to train models that learn from user feedback to improve AI performance in real-world scenarios.

Rich message Business Chatbots in Angular 8 with Dialogflow

Implement a cognitive service for performing language detection on an IoT Edge device. Describe the components and steps for implementing a cognitive service on an IoT Edge device.

Use components to easily share and reuse code and use component-based pipelines to create machine learning workflows.

Use the Azure Machine Learning CLI (v2) to train models as jobs. Train a model using a basic Python script, or perform hyperparameter tuning with a sweep job.

Use Azure Data Factory to add data that resides inside or outside the Azure platform into your search indexes.

Learn best practices for ensuring security and privacy in AI applications and data handling.

Study techniques for data segmentation and clustering to uncover patterns and insights in datasets.

More complex models often can be manually customized to improve how effective they are. Through exercises and explanatory content, we explore how altering the architecture of more complex models can bring about more effective results.

In this module, you'll learn how to set up and configure an x86-based Ubuntu 18.04 system to host an NVIDIA DeepStream development environment.