CGit is now a provider of NVIDIA DLI Hands-On Training!

2 månader sedan

We are happy to announce that CGit will, from now on, offer teacher-led workshops in collaboration with NVIDIA. These workshops consists of hands-on training as well as lectures delivered by DLI-certified instructors.

 

NVIDIA's Deep Learning Institute (DLI) trains developers, data scientists, and researchers in how to use artificial intelligence and accelerated computation to solve real-world problems in a variety of areas. At the deep-learning courses, you will learn how to train, optimize and deploy neural networks. In the accelerated calculation courses, you will learn how to assess, parallelize, optimize and deploy GPU accelerated applications. The courses can be held almost anywhere and with a maximum number of participants of 20 people per occasion. All courses are in English.

Course start takes place no earlier than 6 weeks after booking. Below are examples of teacher-led courses. If you are interested in the entire range, please contact us and we will tell you more.

 

”Fundamentals of Deep Learning for Computer vision”

Explore the fundamentals of deep learning by training neural networks and using results to improve performance and capabilities. Learn how to start solving problems with deep learning.

Prerequisites: None

Frameworks: Caffe

 

“Fundamentals of Deep Learning for Natural Language Processing”

Explore the latest techniques for understanding textual input using natural language processing (NLP). You’ll learn how to convert text to machine understandable representation and train Machine Translators from one language to another.

Prerequisites: Basic experience with neural networks

Frameworks: TensorFlow, Keras

 

Fundamentals of Deep Learning for Multi-GPUs

Learn how to use multiple GPUs to train neural networks and effectively parallelise training of deep neural networks using TensorFlow

Prerequisites: Experience with stochastic gradient descent mechanics

Frameworks: TensorFlow

 

Branschsfokuserade kurser

 

Deep Learning for Autonomous Vehicles – Perception

Learn how to design, train, and deploy deep neural networks for autonomous vehicles using the NVIDIA DRIVE PX development platform. Create and optimize perception components for autonomous vehicles using NVIDIA DRIVE PX.

Prerequisites: Experience with CNNs

Frameworks: TensorFlow, DIGITS, TensorRT

 

Deep Learning for Finance Trading Strategy

Finance trading strategies can be advanced with the power of deep neural networks. Learn how to use time series financial data to make predictions and exploit arbitrage using neural networks.

Prerequisites: Experience with neural networks and knowledge of the financial industry

Frameworks: TensorFlow

 

Deep Learning for Digital Content Creation with Autoencoders

Learn how to animate characters with phase-function neural networks, explore techniques to make arbitrary photo and video style transfer, and train your won denoiser for rendered images.

Prerequisites: Experience with CNNs

Frameworks: Torch, TensorFlow

 

Deep Learning for Healthcare image Analysis

Learn how to apply convolutional neural networks (CNNs) to MRI scans to perform a variety of medical tasks and calculations.

Prerequisites: Basic Experience with CNNs and Python

Frameworks: Caffe, DIGITS, MXNet, TensorFlow

 

Deep Learning for Healthcare Genomics

Learn how convolutional neural networks (CNNs) work and how to apply deep learning to detect chromosome co-deletion and search for motifs in genomic sequences.

Prerequisites: Basic Experience with CNNs and Python

Frameworks: Caffe, TensorFlow, Theano

 

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