This Week in Machine Learning & Artificial Intelligence (AI) Podcast
About This Show
This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders. These creators, builders, makers and influencers value TWiML as an authentic, trusted and insightful guide to all that’s interesting and important in the world of machine learning and AI.
Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.
Most Recent Episode
Training Data for Computer Vision at Figure Eight with Qazaleh Mirsharif - TWiML Talk #144
1 day ago
For today’s show, the last in our TrainAI series, I'm joined by Qazaleh Mirsharif, a machine learning scientist working on computer vision at Figure Eight.
Qazaleh and I caught up at the TrainAI conference to discuss a couple of the projects she’s worked on in that field, namely her research into the classification of retinal images and her work on parking sign detection from Google Street View images. The former, which attempted to diagnose diseases like diabetic retinopathy using retinal scan images, is similar to the work I spoke with Ryan Poplin about on TWiML Talk #122. In my conversation with Qazaleh we focus on how she built her datasets for each of these projects and some of the key lessons she’s learned along the way.
The notes for this show can be found at twimlai.com/talk/144.
For series details, visit twimlai.com/trainai2018.
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Rated 5 out of
I am a student in a small college that doesn't have much in terms of computer science, and my degree path is more focused on IT. I have become enamored with machine learning over the past year or so and listen to a lot of podcasts, both during downtime and while driving. This is one of the best I have come across and each episode I learn something new.
Date published: 2017-08-03