The Netflix TechBlog
MARCH 7, 2024
For ETL and other heavy lifting of data, we mainly rely on Apache Spark. In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training. Correspondingly, each application brings its own bespoke set of dependencies.
Dynatrace
JULY 6, 2022
AI that is based on machine learning needs to be trained. This requires significant data engineering efforts, as well as work to build machine-learning models. While automating IT processes without integrated AIOps can create challenges, the approach to artificial intelligence itself can also introduce potential issues.
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The Netflix TechBlog
MARCH 4, 2024
Service Integrations Figure 2 illustrates the integration of the services generating and applying the recommendations in the data platform. The major services are as follows: Nightingale is a service running the ML model trained using Metaflow and is responsible for generating a retry recommendation.
O'Reilly
SEPTEMBER 15, 2021
Most respondents participated in training of some form. Learning new skills and improving old ones were the most common reasons for training, though hireability and job security were also factors. Company-provided training opportunities were most strongly associated with pay increases. Demographics. Salaries by Gender.
The Netflix TechBlog
OCTOBER 18, 2022
by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.
O'Reilly
NOVEMBER 26, 2024
They don’t respond to changes quickly, and that leaves them particularly vulnerable when providing training for industries where change is rapid. Staying current in the tech industry is a bit like being a professional athlete: You have to train daily to maintain your physical conditioning.
The Netflix TechBlog
SEPTEMBER 18, 2020
A role in data science eventually seemed like a natural transition, but it wasn’t without its hurdles: With my consulting background, I had to go through a few other roles first while learning how to code on the side. Tell me about some of the exciting projects you’re a part of.
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