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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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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Uber expanded Michelangelo “to serve any kind of Python model from any source to support other Machine Learning and Deep Learning frameworks like PyTorch and TensorFlow [instead of just using Spark for everything].”. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

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Natural Language Processing: A Guide to NLP Use Cases, Approaches, and Tools

Altexsoft

Sentiment analysis results by Google Cloud Natural Language API. People are doing NLP projects all the time and they’re publishing their results in papers and blogs. Use your own knowledge or invite domain experts to correctly identify how much data is needed to capture the complexity of the task. Open-source toolkits.

Tools 139
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Demystifying MLOps: From Notebook to ML Application

Xebia

In this blog post, we’ll try to demystify MLOps and take you through the process of going from a notebook to your very own industry-grade ML application. Data science is generally not operationalized Consider a data flow from a machine or process, all the way to an end-user. What is this thing called MLOps ?

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Monitoring dbt model and test executions using Elementary Data

Xebia

Let’s imagine we are running dbt as a container within a cloud run job (a cloud-native container runtime within Google Cloud). Every morning when all the raw source data is ingested, we spin up a container via a trigger to do our daily data transformation workload using dbt.

Testing 130
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Technology Trends for 2024

O'Reilly Media - Ideas

Rachel Stephens provides two fascinating pieces of the puzzle in a recent article on the RedMonk blog , but those pieces don’t fit together exactly. Our own theory is that it’s a reaction to GPT models leaking proprietary code and abusing open source licenses; that could cause programmers to be wary of public code repositories.

Trends 120
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The Good and the Bad of Apache Airflow Pipeline Orchestration

Altexsoft

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. Source: Apache Airflow.