• AI Data Workflow Forum W/ Chris Dwan - Raleigh

    Tobacco Road Sports Cafe

    I wanted to share this FREE data workflow forum we're hosting in Raleigh, NC with you guys. It's a great opportunity to listen to Chris Dwan, a technologist, and consultant specializing in scientific computing and data architecture for the life sciences speak on topics focused around accelerating diagnostic workflows with AI/ML. Come to connect with peers in the greater research triangle area! If you're unfamiliar with Chris, his LinkedIn can be found below. Summarizing his accomplishments, he directed the research computing team at the Broad Institute and previously built the infrastructure for the New York Genome Center. Event Registration: https://www.ncbiotech.org/events/igneous-data-workflow-forum-accelerating-diagnostic-workflows-ai Or just email me: [masked] I am happy to answer any questions regarding the event. Hope to see some of you there! Event details: Time: 4-7PM Date: November 1st Place: Tobacco Road Sports Cafe & Brewery Chris Dwans LinkedIn: https://www.linkedin.com/in/chris-dwan/

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  • Deep Learning Study Group - fast.ai

    The Frontier RTP

    Bring a laptop and let's study together. Practical Deep Learning For Coders (http://course.fast.ai/) from fast.ai. Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. It's totally free! (but you might end up paying AWS about $20 to use their GPU servers) [Course Link] (http://course.fast.ai/) [First Lecture] (https://www.youtube.com/watch?v=Th_ckFbc6bI) Come on down to ask and answer questions if you get stuck working through the labs. They say the best way to learn is to teach. So I've made it through the first three weeks and am happy to share what I learned. Everyone is welcome (http://www.fast.ai/2016/10/08/course-background/). This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step one—learning how to get a GPU server online suitable for deep learning—and go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems. There are around 20 hours of lessons, and you should plan to spend around 10 hours a week for 7 weeks to complete the material (http://www.fast.ai/2016/10/08/curriculum/).

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  • Deep Learning Study Group - fast.ai

    American Underground @ Main

    Bring a laptop and let's study together. Practical Deep Learning For Coders (http://course.fast.ai/) from fast.ai. Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. It's totally free! (but you might end up paying AWS about $20 to use their GPU servers) [Course Link] (http://course.fast.ai/) [First Lecture] (https://www.youtube.com/watch?v=Th_ckFbc6bI&t=2598s) Please watch the first lecture, then come on down to ask and answer questions if you get stuck. They say the best way to learn is to teach. So I've made it through the first three weeks and am happy to share what I learned. Everyone is welcome. (http://www.fast.ai/2016/10/08/course-background/) This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step one—learning how to get a GPU server online suitable for deep learning—and go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems. There are around 20 hours of lessons, and you should plan to spend around 10 hours a week for 7 weeks to complete the material (http://www.fast.ai/2016/10/08/overview/).

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  • Deep Learning Study Group - fast.ai

    Hunt Library at NCSU Centennial Campus

    Bring a laptop and let's study together. Room 4411 Practical Deep Learning For Coders (http://course.fast.ai/) from fast.ai. Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. It's totally free! (but you might end up paying AWS about $20 to use their GPU servers) [Course Link] (http://course.fast.ai/) [First Lecture] (https://youtu.be/kzt3-FHdAeM) Come on down to ask and answer questions if you get stuck working through the labs. They say the best way to learn is to teach. So I've made it through the first three weeks and am happy to share what I've learned. Everyone is welcome (http://www.fast.ai/2016/10/08/course-background/). This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step one—learning how to get a GPU server online suitable for deep learning—and go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems. There are around 20 hours of lessons, and you should plan to spend around 10 hours a week for 7 weeks to complete the material (http://www.fast.ai/2016/10/08/curriculum/).

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  • Deep Learning Study Group - fast.ai

    The Frontier RTP

    Bring a laptop and let's study together. Practical Deep Learning For Coders (http://course.fast.ai/) from fast.ai. Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. It's totally free! (but you might end up paying AWS about $20 to use their GPU servers) [Course Link] (http://course.fast.ai/) [First Lecture] (https://www.youtube.com/watch?v=Th_ckFbc6bI) Come on down to ask and answer questions if you get stuck working through the labs. They say the best way to learn is to teach. So I've made it through the first three weeks and am happy to share what I learned. Everyone is welcome (http://www.fast.ai/2016/10/08/course-background/). This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step one—learning how to get a GPU server online suitable for deep learning—and go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems. There are around 20 hours of lessons, and you should plan to spend around 10 hours a week for 7 weeks to complete the material (http://www.fast.ai/2016/10/08/curriculum/).

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  • Deep Learning Study Group - fast.ai

    Hunt Library at NCSU Centennial Campus

    Let's study together. Practical Deep Learning For Coders (http://course.fast.ai/), is a new course, taught by Jeremy Howard (Kaggle (https://www.kaggle.com/)'s #1 competitor 2 years running, and founder of Enlitic (http://www.enlitic.com/)). Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. Oh and one other thing... it's totally free! (but you might end up paying AWS about $20 to use their GPU servers) http://course.fast.ai/ Come on down to ask and answer questions if you get stuck working through the labs. I've made it through the first three weeks and am happy to share what I learned so far. They say the best way to learn is to teach. Everyone is welcome (https://www.youtube.com/watch?v=kzt3-FHdAeM&authuser=0). This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step one—learning how to get a GPU server online suitable for deep learning—and go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems. There are around 20 hours of lessons, and you should plan to spend around 10 hours a week for 7 weeks to complete the material. The course is based on lessons recorded during the first certificate course at The Data Institute at USF. Part 2 will be taught at the Data Institute from Feb 27, 2017, and will be available online around May 2017.

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  • Deep Learning Study Group - fast.ai

    The Frontier RTP

    Let's study together. Practical Deep Learning For Coders (http://course.fast.ai/), is a new course, taught by Jeremy Howard (Kaggle's (http://www.kaggle.com/) #1 competitor 2 years running, and founder of Enlitic (http://www.enlitic.com/)). Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. Oh and one other thing... it's totally free! (but you might end up paying AWS about $20 to use their GPU servers) http://course.fast.ai/ Come on down to ask and answer questions if you get stuck working through the labs. They say the best way to learn is to teach. So I've made it through the first three weeks and am happy to share what I learned. Everyone is welcome. This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step one—learning how to get a GPU server online suitable for deep learning—and go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems. There are around 20 hours of lessons, and you should plan to spend around 10 hours a week for 7 weeks to complete the material. The course is based on lessons recorded during the first certificate course at The Data Institute at USF (https://www.usfca.edu/data-institute/). Part 2 will be taught at the Data Institute from Feb 27, 2017, and will be available online around May 2017.

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  • Deep Learning in the Life Sciences

    Needs a location

    There will be a truncated presentation on Deep Learning in the Life Sciences (10 mins) as part of a Data4Good (https://www.meetup.com/NC-Data4Good/events/236796192/)meetup (https://www.meetup.com/NC-Data4Good/events/236796192/). The Data4Good Initiative would like to form a team to compete in Kaggle's Data Science Bowl (https://www.kaggle.com/c/data-science-bowl-2017) - and this year's competition is to accurately diagnose lung cancer in CT images. Deep learning has been very effective solving these (http://www.enlitic.com/) types (http://www.benevolent.ai/) of problems so far (https://www.youtube.com/embed/GTs5ZQ6XwUM). This will not be a stand-alone talk or meetup - please see the details on the Data4Good meetup (https://www.meetup.com/NC-Data4Good/events/236796192/) page. https://www.meetup.com/NC-Data4Good/events/236796192/

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  • Deep Learning Study Group - fast.ai

    The Frontier RTP

    Let's study together. Practical Deep Learning For Coders (http://course.fast.ai/), is a new course, taught by Jeremy Howard (Kaggle's (http://www.kaggle.com/) #1 competitor 2 years running, and founder of Enlitic (http://www.enlitic.com/)). Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. Oh and one other thing... it's totally free! http://course.fast.ai/ Come on down to ask and answer questions if you are working through the labs. They say the best way to learn is to teach. So I've made it through the first two weeks and I'm happy to share what I learned. Everyone is welcome. If you can't make it in person, we are going to host a Google Hangout during the session. Stay tuned for details.

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  • Deep Learning Study Group - fast.ai

    The Frontier RTP

    Let's study together. Practical Deep Learning For Coders (http://course.fast.ai/), is a new course, taught by Jeremy Howard (Kaggle's (http://www.kaggle.com/) #1 competitor 2 years running, and founder of Enlitic (http://www.enlitic.com/)). Learn how to build state of the art models without needing graduate-level math—but also without dumbing anything down. Oh and one other thing... it's totally free! http://course.fast.ai/ Come on down to ask and answer questions if you are working through the labs. They say the best way to learn is to teach. So I've made it through the first two weeks and I'm happy to share what I learned. Everyone is welcome. If you can't make it in person, we are going to host a Google Hangout during the session. Stay tuned for details.

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