Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. Below are 20 essential tools every data engineer should know.

Data Engineering 52

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DagsHub

DECEMBER 11, 2023

Using data versioning can make it possible to have the snapshot of the training data and experimentation results to make the implementation easier at each iteration. The above challenges can be tackled by using the following eight data version control tools.

Machine Learning 98

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Iguazio

DECEMBER 18, 2023

This means that in 2024, we’re likely to see businesses continue to seek ways to adopt generative AI as a way to enhance their operations. Will generative AI continue to be one of the hottest topics in 2024 as well? In 2024, I expect to see a growing focus on accuracy during AI model development and deployment.

ML 64

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Iguazio

DECEMBER 18, 2023

This means that in 2024, we’re likely to see businesses continue to seek ways to adopt generative AI as a way to enhance their operations. Will generative AI continue to be one of the hottest topics in 2024 as well? In 2024, I expect to see a growing focus on accuracy during AI model development and deployment.

ML 52

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Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

DagsHub

APRIL 21, 2024

Best MLOps Tools & Platforms for 2024 In this section, you will learn about the top MLOps tools and platforms that are commonly used across organizations for managing machine learning pipelines. Data storage and versioning Some of the most popular data storage and versioning tools are Git and DVC.

Machine Learning 59

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DagsHub

DECEMBER 5, 2023

The Git integration means that experiments are automatically reproducible and linked to their code, data, pipelines, and models. With DVC, we don't need to rebuild previous models or data modeling techniques to achieve the same past state of results.

Machine Learning 52

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