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Software engineering for machine learning: a case study

The Morning Paper

Software engineering for machine learning: a case study Amershi et al., More specifically, we’ll be looking at the results of an internal study with over 500 participants designed to figure out how product development and software engineering is changing at Microsoft with the rise of AI and ML. ICSE’19.

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A Day in the Life of… a Software Training Specialist

Tasktop

Meet Jason Grodan, a Software Training Specialist at Tasktop! We spoke to Jason about the different training classes Tasktop offers, bouldering, and what it’s like to work from home. My role at Tasktop is a ‘Software Training Specialist’. We provide training for Customers and Partners as well as new employees.

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All of Netflix’s HDR video streaming is now dynamically optimized

The Netflix TechBlog

HDR was launched at Netflix in 2016 and the number of titles available in HDR has been growing ever since. A vital aspect of such development is subjective testing with HDR encodes in order to generate training data. As noted in an earlier blog post , we began developing an HDR variant of VMAF; let’s call it HDR-VMAF. Krasula, A.

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The 737Max and Why Software Engineers Might Want to Pay Attention

J. Paul Reed

The 737Max and Why Software Engineers Might Want to Pay Attention As someone with a bit of a reputation for talking about aviation and software development and operations , I’ve been asked about the 737Max repeatedly over the past week. a selling point ?—?and

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SKP's Java/Java EE Gotchas: Clash of the Titans, C++ vs. Java!

DZone

As a Software Engineer, the mind is trained to seek optimizations in every aspect of development and ooze out every bit of available CPU Resource to deliver a performing application. Most of us, as we spend years in our jobs — tend to be proficient in at least one of these.

Java 207
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Evolution of ML Fact Store

The Netflix TechBlog

We built Axion primarily to remove any training-serving skew and make offline experimentation faster. These facts are managed and made available by services like viewing history or video metadata services outside of Axion. Our machine learning models train on several weeks of data. Time is a critical component of Axion?—?When

Storage 187
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Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

The Netflix TechBlog

mainly because of mundane reasons related to software engineering. On the other hand, very few data scientists feel strongly about the nature of the data warehouse, the compute platform that trains and scores their models, or the workflow scheduler. The steps can be arbitrary Python code.