Hosted by Nvidia, Mark III Systems and NC State OIT, each session features industry experts who will dive into a current trend around Al\/ML via tutorials and hands-on rapid labs. Anyone interested in these topics is welcome to register. Register separately for each session you are interested in attending.<\/p>\n
Series: <\/strong>every other Thursday, February 23 to May 4, 2023 <\/p>\n Thursday, Feb 23rd (11am-12pm ET) In this session, we\u2019ll cover the basics around what Machine Learning is, look at the different ML techniques and methods, examine what a typical ML project lifecycle looks like, and discuss some of the most commonly used example algorithms. This session will also include a 20-minute rapid mini-workshop via Jupyter Notebook where we’ll use an example dataset from Kaggle and take it through the steps of training and evaluating a model to make predictions using ML.\u00a0 Examples of labs that we’ll utilize include forecasts using ML for anomaly detection and for classifying biological states. <\/p>\n Thursday, March 9th (11am-12pm ET) In this session, we’ll cover the basics around what Deep Learning is, look at how it fits within the AI\/ML universe, dive into neural networks (including CNNs, LSTMs, and GANs), and walk through a typical Deep Learning project lifecycle. We’ll cap the session with a 20-minute rapid mini-workshop via Jupyter Notebook where we’ll use an example dataset (CIFAR-10) to train and evaluate a neural network model using Keras for computer vision use cases. <\/p>\n Thursday, March 23rd\u00a0(11am-12pm ET)<\/strong> In this session, we’ll cover what datasets for Machine Learning and Deep Learning projects look like and how to find them. This will include highlighting some of the most popular datasets in the community today as well as good sources to download these datasets from. Some brief tips and tricks for cleaning up datasets will be covered and we’ll conclude the session with a mini-workshop and lab showing how to import and interact with datasets in a Jupyter Notebook to collect and prep data for forecasting and predictions. <\/p>\n Thursday, April 6th\u00a0(11am-12pm ET)<\/strong> In this session, we’ll cover the basics around what computer vision is, how it works (classification, object detection, segmentation), some of the popular frameworks and models used today, and what some of the practical applications might be in research and industry.\u00a0 We’ll also walk through what a typical Computer Vision project lifecycle might look like. We’ll cap the session with a 20-minute rapid mini-workshop via Jupyter Notebook where we’ll use code examples to build a CNN image classifier as well as using pretrained model libraries for object detection and image segmentation. <\/p>\n Thursday, April 20th\u00a0(11am-12pm ET)<\/strong> This session will cover the ML\/DL ecosystem of container-powered technologies and the best ways to get started and accelerate your journey in building, training, deploying, and scaling your models.\u00a0 We’ll touch on NVIDIA NGC, Docker, Kubernetes, Singularity, and other ways to get started and get going quickly. Special focus will be placed on how train models for business analytics use cases and deploy them anywhere where its most impactful and useful for the organization. <\/p>\n Thursday, May 4th\u00a0(11am-12pm ET)<\/strong> In this session, we’ll cover the basics around NVIDIA’s Omniverse platform for 3D Design Collaboration and Simulation and the ecosystem of building Digital Twins.\u00a0 We’ll touch on not only how to set up and rollout an Omniverse environment, but also how to integrate frameworks, like Modulus (physics simulations) and Isaac (robotics) into Omniverse to visualize your models and research.\u00a0 Whether you’re in a School of Engineering, Architecture, Natural Sciences, Computer Science, Business, or Data Science, we’ll have something for you in this session.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":" Hosted by Nvidia, Mark III Systems and NC State OIT, each session features industry experts who will dive into a current trend around Al\/ML via tutorials and hands-on rapid labs. 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\nTime:<\/strong> 11 a.m. \u2013 12 p.m.
\nLocation:<\/strong>\u00a0Virtual<\/p>\n
\n<\/strong>Intro to Machine Learning and AI:\u00a0 The Basics, A Tutorial, and Lab
\n<\/strong>Speaker:\u00a0<\/strong>Data Scientist, Mark III<\/p>\n<\/div>\n<\/div>\n<\/div>\n
\nRegister Now<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n<\/strong>Intro to Deep Learning: An Introduction to Neural Networks
\n<\/strong>Speaker:<\/strong>\u00a0Data Scientist, Mark III<\/p>\n<\/div>\n<\/div>\n<\/div>\n
\nRegister Now<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\nIntroduction to Datasets
\n<\/strong>Speaker:<\/strong>\u00a0Data Scientist, Mark III<\/p>\n<\/div>\n<\/div>\n<\/div>\n
\nRegister Now<\/a><\/p>\n
\nIntro to Computer Vision and Image Analytics
\n<\/strong>Speaker:<\/strong>\u00a0Data Scientist, Mark III<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\nRegister Now<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\nGetting Started with Containers and AI
\n<\/strong>Speakers:\u00a0<\/strong>Architects,\u00a0NVIDIA, Mark III<\/p>\n<\/div>\n<\/div>\n<\/div>\n
\nRegister Now<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\nIntro to Omniverse & Digital Twins
\n<\/strong>Speakers:\u00a0<\/strong>Innovation, Mark III & NVIDIA<\/p>\n<\/div>\n<\/div>\n<\/div>\n