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NVIDIA is a world leader in Visual Computing, it was born in the field of video games and is famous for breathtaking interactive graphics. Today, it is a fundamental component in all sectors where high computing power is required.
The NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI, accelerated computing, and accelerated data science.
NVIDIA Recognized Extpertise Certification
Deep Learning for Multiple Data Types
Accelerated Computing with CUDA C/C++
Accelerated Computing with CUSA Python
GPU Virtualization Product
GPU Virtualization Sales
Explore the fundamentals of Deep Learning by training neural networks and using results to improve performance and capabilities. In this course, you’ll learn the basics of deep learning by training and deploying neural networks.
The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs. Upon completion, you’ll be able to accelerate and optimize existing C/C++ CPU-only applications using the most essential CUDA tools and techniques. You’ll understand an iterative style of CUDA development that will allow you to ship accelerated applications fast.
This course explores how to use Numba to accelerate Python programs to run on massively parallel NVIDIA GPUs. Upon completion, you’ll be able to use Numba to compile and launch CUDA kernels to accelerate your Python applications on NVIDIA GPUs.
In this workshop you will learn how to develop end-to-end Machine Learning pipelines and accelerate them using GPU in order to speed up the phases of data exploration, preprocessing, prototyping, training and inference of Machine Learning models.
All this is made possible by RAPIDS, an open-source, easy to use library that implements the most important algorithms exploiting GPU, using less training time and resulting in a reduction in costs.
Natural Language Processing applications (NLP) have grown significantly in recent years touching multiple industries from manufacturing to finance.
Modern techniques are able to understand the meaning of the text as well as the linguistic nuances, tone and context, just like humans! In this workshop you will find out how to classify text and do Named-entity recognition (NER) using state-of-the-art models. Finally, it will be explained how to deploy these neural networks in order to be ready to be used in production.
Find out how to build a recommendation engine with neural networks to improve and personalize the user experience of your customers. We will implement both content-based recommendation systems and those that exploit collaborative filtering algorithms (ALS) and then conclude with the more generic and complex ones such as "Deep and wide" using Tensorflow 2. Finally, the most suitable tools to deploy the models and create real-time solutions will be presented. Read more
Machine Learning Reply is specialized in providing AI services and solutions to guide its customers towards digitalisation, helping them to become more competitive and data driven as a result of Smart Analytics, Machine Learning and Artificial Intelligence.
The consultative approach, the functional expertise and the highly specialized technological components are the key enablers through which Machine Learning Reply builds a tailored proposal, to meet the needs of the market and the individual customer. The company operates in the main industries offering itself as a reference point in facing digital challenges. The collaboration with prestigious technological and institutional partners allows the company to remain aligned with the main sector trends and consequently offer products and services in line with the highest market standards.