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Databricks Partners with Google Cloud to Deliver its Platform to Global Businesses

DevOps.com

Databricks launches on Google Cloud with integrations to Google BigQuery and AI Platform that unify data engineering, data science, machine learning, and analytics across both companies’ services Sunnyvale and San Francisco, Calif., Under the […].

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7 Free Google Cloud Training Resources

ParkMyCloud

If you’re looking to break into the cloud computing space, or just continue growing your skills and knowledge, there are an abundance of resources out there to help you get started, including free Google Cloud training. Google Cloud Free Program. GCP’s free program option is a no-brainer thanks to its offerings. .

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What is Machine Learning Engineer: Responsibilities, Skills, and Value Brought

Altexsoft

In a world fueled by disruptive technologies, no wonder businesses heavily rely on machine learning. Google, in turn, uses the Google Neural Machine Translation (GNMT) system, powered by ML, reducing error rates by up to 60 percent. The role of a machine learning engineer in the data science team.

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MLOps: Methods and Tools of DevOps for Machine Learning

Altexsoft

When speaking of machine learning, we typically discuss data preparation or model building. Living in the shadow, this stage, according to the recent study , eats up 25 percent of data scientists time. MLOps lies at the confluence of ML, data engineering, and DevOps. More time for development of new models.

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

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What is a data architect? Skills, salaries, and how to become a data framework master

CIO

Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence. Data architect vs. data engineer The data architect and data engineer roles are closely related.

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Predibase exits stealth with a low-code platform for building AI models

TechCrunch

“The major challenges we see today in the industry are that machine learning projects tend to have elongated time-to-value and very low access across an organization. “Given these challenges, organizations today need to choose between two flawed approaches when it comes to developing machine learning. .