Infrastructure Processing Software Engineering Training 
Strategic Tech
MARCH 16, 2021
There are a few qualities that differentiate average from high performing software engineering organisations. In my experience, the culture is better and the results are better in orgs where engineers and architects obsess over the design of code and architecture. My experience is the opposite.
The Morning Paper
JULY 7, 2019
Software engineering for machine learning: a case study Amershi et al., Previously on The Morning Paper we’ve looked at the spread of machine learning through Facebook and Google and some of the lessons learned together with processes and tools to address the challenges arising. A general process. ICSE’19.
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The Netflix TechBlog
NOVEMBER 29, 2023
A vital aspect of such development is subjective testing with HDR encodes in order to generate training data. For a given rate-quality operating point, the DO process helps allocate bits among the various shots while maximizing an overall objective function. Krasula, A. Choudhury, S. Malfait, A. 263–1–8 (2023) [ online ] [2] A.
Tasktop
FEBRUARY 20, 2020
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.
The Netflix TechBlog
DECEMBER 3, 2019
About two years ago, we, at our newly formed Machine Learning Infrastructure team started asking our data scientists a question: “What is the hardest thing for you as a data scientist at Netflix?” mainly because of mundane reasons related to software engineering. like they would do in a Jupyter notebook.
High Scalability
JANUARY 11, 2022
FUN FACT : In this talk , Rodrigo Schmidt, director of engineering at Instagram talks about the different challenges they have faced in scaling the data infrastructure at Instagram. There are two major processes which gets executed when a user posts a photo on Instagram. System Components. Streaming Data Model. Optimization.
The Netflix TechBlog
APRIL 26, 2022
We built Axion primarily to remove any training-serving skew and make offline experimentation faster. We make sure there is no training/serving skew by using the same data and the code for online and offline feature generation. Our machine learning models train on several weeks of data.
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