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New Series: Creating Media with Machine Learning

Netflix Tech

By Vi Iyengar , Keila Fong , Hossein Taghavi , Andy Yao , Kelli Griggs , Boris Chen , Cristina Segalin , Apurva Kansara , Grace Tang , Billur Engin , Amir Ziai , James Ray , Jonathan Solorzano-Hamilton Welcome to the first post in our multi-part series on how Netflix is developing and using machine learning (ML) to help creators make better media?—?from

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10 highest-paying IT skills for 2024

CIO

These roles include data scientist, machine learning engineer, software engineer, research scientist, full-stack developer, deep learning engineer, software architect, and field programmable gate array (FPGA) engineer. It is used to execute and improve machine learning tasks such as NLP, computer vision, and deep learning.

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All about Machine Learning

Hacker Earth Developers Blog

In our third episode of Breaking 404 , we caught up with Srivatsan Ramanujam, Director of Software Engineering: Machine Learning, Salesforce to discuss everything about Machine Learning and the best practices for ML engineers to excel in their careers. Again, focus on Data Science and Machine Learning.

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Sneaker fit startup Neatsy.ai gets $1M seed after B2B pivot

TechCrunch

startup, which was founded back in March 2019 by Artem Semyanov (the former head of the machine learning team at Prism Labs ), is now fully focused on selling its fit-tech to e-tailers via an SDK. Neatsy wants to reduce sneaker returns with 3D foot scans. “We are also looking at the U.S.

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How Nvidia became a trillion-dollar company

CIO

Its founders spotted that generating 3D graphics in video games—then a fast-growing market—placed highly repetitive, math-intensive demands on PC central processing units (CPUs). Although Nvidia’s first chips were used to enhance 3D gaming, the manufacturing industry is also interested in 3D simulations, and its pockets are deeper.

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Making Life Easier Through Machine Learning

Robots and Pencils

You’re only as smart as what you’re taught The first thing we need to do with machine learning is to train our model. But in order to have better accuracy when it comes to prediction, you need A LOT of test images. For 3D objects like faces it doesn’t do a good job. Testing So, how did we do? Let’s get started!

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Prellis Biologics raises $14.5M, debuts a ‘human immune system’ in a dish

TechCrunch

Prellis Biologics , a company developing the tools to create 3D-printed organs, announced a $14.5 Up until this point, Prellis has focused on 3D printing vascular scaffolds that would allow companies to grow healthy and oxygenated human organs (or miniature versions, called organoids) for drug testing, and eventually transplant.

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