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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system.

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How to Become Databricks Certified Apache Spark Developer?

ProjectPro

With around 35k stars and over 26k forks on Github, Apache Spark is one of the most popular big data frameworks used by 22,760 companies worldwide. Apache Spark is the most efficient, scalable, and widely used in-memory data computation tool capable of performing batch-mode, real-time, and analytics operations.

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Building Real-time Machine Learning Foundations at Lyft

Lyft Engineering

In this blog post, we will discuss what we built in support of that goal and some of the lessons we learned along the way. Capabilities of Real-time Machine Learning One of the first questions we asked ourselves is — what are the general use cases within the ML ecosystem that can leverage streaming data?

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Cloudera DataFlow’s key milestones and wins in 2020

Cloudera

Everyone was looking for real-time insights by analyzing what is going on currently within their businesses and taking corrective action pro-actively. Everyone was looking for real-time insights by analyzing what is going on currently within their businesses and taking corrective action pro-actively.

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Data Engineering Annotated Monthly – October 2021

Big Data Tools

Here’s what’s happening in the world of data engineering right now. Apache Spark® has been released and there are a load of changes, including ANSI SQL support, Pandas API layer over PySpark, and lots and lots of other things. If you’re wondering what Timetables are, check out the Articles section below for a nice description.

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Data Engineering Annotated Monthly – October 2021

Big Data Tools

Here’s what’s happening in the world of data engineering right now. Apache Spark® has been released and there are a load of changes, including ANSI SQL support, Pandas API layer over PySpark, and lots and lots of other things. If you’re wondering what Timetables are, check out the Articles section below for a nice description.

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Data Engineers of Netflix?—?Interview with Pallavi Phadnis

Netflix Tech

Pallavi, what’s your journey to data engineering at Netflix? Netflix’s unique work culture and petabyte-scale data problems are what drew me to Netflix. Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix.