Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

Deep learning has revolutionized NLP and problems that require a large amount of work in terms of new features. Tuning can now be efficiently solved using NLP.

Understand ethical challenges in generative AI. Learn about challenges, risks, data privacy, algorithmic bias, and decision-making frameworks for responsible use.

Unlock the power of generative AI responsibly. This course will teach you generative AI prototyping, evaluation concepts, principles, and ethical considerations.

Neural networks are the foundation for so many applications in the field of machine learning and artificial intelligence. This course will demystify what they are, how they work, and how they can be used in a variety of real-world applications.

Unlock the power of neural networks in data science. This course will teach you to build, deploy, and optimize neural networks for real-world applications.

Unlock the potential of image classification with neural networks. This course will teach you to extract features, build, and evaluate models using TensorFlow, and explore advanced architectures with transfer learning.

Transformers have revolutionized NLP since their inception in 2017. They can understand language at a deeper level as well as parallelize training on GPUs. In this course, you will learn how to create Transformers for NLP.

With NVIDIA DeepStream, you can seamlessly develop optimized Intelligent Video Applications that can consume multiple video, image, and audio sources. You can also apply single or cascading inference operations to video frames in real-time, and transmit inference results to the cloud for archiving or additional processing.

In this module, you'll publish and deploy an ARM-based DeepStream container workload to NVIDIA embedded hardware by using Azure IoT Edge.

Use a Live Video Analytics module to deploy a machine learning solution to an IoT Edge device. The solution will process a video feed from cameras and detect objects at the edge using a YOLO model to perform inferencing operations. Check that the solution is successfully deployed and test your solution from a web application.

Computer vision applications can automate and enhance the analysis and interpretation of visual data beyond human capabilities. This course will teach you how image classifiers can perform object detection recognition and tracking using Tensorflow.