ODSC - Open Data Science

JULY 22, 2023

The week was filled with engaging sessions on top topics in data science, innovation in AI, and smiling faces that we haven’t seen in a while. On Wednesday, Henk Boelman, Senior Cloud Advocate at Microsoft, spoke about the current landscape of Microsoft Azure, as well as some interesting use cases and recent developments.

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Apache Kafka Machine Learning Machine Learning Data Science 52

ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. As MLOps become more relevant to ML demand for strong software architecture skills will increase as well.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

ODSC - Open Data Science

MAY 31, 2023

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

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Data Lakes Machine Learning Machine Learning Apache Kafka 131

ODSC - Open Data Science

MAY 8, 2023

Article on Azure ML by Bethany Jepchumba and Josh Ndemenge of Microsoft In this article, I will cover how you can train a model using Notebooks in Azure Machine Learning Studio. When uploading your data, you specify the Machine Learning type, test, and training data before training. Let us get started!

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Azure ML ML Data Modeling 52

ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

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Data Lakes Azure Hadoop Data Warehouse 52

ODSC - Open Data Science

APRIL 3, 2023

Data analysts often must go out and find their data, process it, clean it, and get it ready for analysis. This pushes into Big Data as well, as many companies now have significant amounts of data and large data lakes that need analyzing. Cloud Services: Google Cloud Platform, AWS, Azure.

Analytics 52

Analytics Analytics Data Analyst SQL 52

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Data Warehouse Cloud Data Database Analytics 57

ODSC - Open Data Science

APRIL 27, 2023

5 Concerns for ML Safety in the Era of LLMs and Generative AI The growth of large language models and generative AI has spurred new concerns for ML safety and cybersecurity. 5 Data Engineering and Data Science Cloud Options for 2023 AI development is incredibly resource intensive.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data fabric: A mostly new architecture.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

DagsHub

DECEMBER 11, 2023

DVC Released in 2017, Data Version Control ( DVC for short) is an open-source tool created by iterative. DVC can be used for versioning data and models, to track experiments and compare any data, code, parameters models and graphical plots of performance. DVC can efficiently handle large files and machine learning models.

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Machine Learning Machine Learning Data Lakes Database 98

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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Machine Learning Machine Learning ML ML 134

Tableau

FEBRUARY 17, 2021

Upgrade to take advantage of these new innovations, and learn more about how Tableau brings AI into analytics to help users across your organization answer pressing questions. Enjoy significant Azure connectivity improvements to better optimize Tableau and Azure together for analytics. Microsoft Azure connectivity improvements.

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Tableau Azure Data Quality ML 99

Tableau

FEBRUARY 17, 2021

Upgrade to take advantage of these new innovations, and learn more about how Tableau brings AI into analytics to help users across your organization answer pressing questions. Enjoy significant Azure connectivity improvements to better optimize Tableau and Azure together for analytics. Microsoft Azure connectivity improvements.

Tableau 52

Tableau Azure Data Quality ML 52

O'Reilly Media

OCTOBER 19, 2021

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. What does a modern technology stack for streamlined ML processes look like? Why: Data Makes It Different. All ML projects are software projects.

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ML ML Data Scientist AWS 138

Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used.

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Data Governance ML ML Cloud Data 59

The MLOps Blog

OCTOBER 20, 2023

Nevertheless, many data scientists will agree that they can be really valuable – if used well. And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. Aside neptune.ai

SQL 52

SQL Database Data Scientist Python 52

Alation

JULY 18, 2022

Are your data users overwhelmed by silos and frustrated by untrusted data? Tell them to grab a catalog … and go jump in a lake. That was the message — delivered a little more elegantly than that — at Databricks’ Data+AI Summit 2022. A simple model to control access to data via a UI or SQL. and much more!

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AI AI Data Lakes Azure 52

The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

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Machine Learning Machine Learning Data Scientist ML 69