O'Reilly Media

OCTOBER 19, 2021

We need robust versioning for data, models, code, and preferably even the internal state of applications—think Git on steroids to answer inevitable questions: What changed? Prior to the cloud, setting up and operating a cluster that can handle workloads like this would have been a major technical challenge.

ML 145

ML ML Data Scientist AWS 145

Mlearning.ai

FEBRUARY 16, 2023

The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data. The solution was built on top of Amazon Web Services and is now available on Google Cloud and Microsoft Azure. Use Multiple Data Models With on-premise data warehouses, storing multiple copies of data can be too expensive.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Pickl AI

JUNE 7, 2024

Read More: Advanced SQL Tips and Tricks for Data Analysts. Hadoop Hadoop is an open-source framework designed for processing and storing big data across clusters of computer servers. It serves as the foundation for big data operations, enabling the storage and processing of large datasets.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

DagsHub

APRIL 21, 2024

Scikit-learn provides a consistent API for training and using machine learning models, making it easy to experiment with different algorithms and techniques. It also provides tools for model evaluation , including cross-validation, hyperparameter tuning, and metrics such as accuracy, precision, recall, and F1-score.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Pickl AI

JULY 25, 2023

Model Development Data Scientists develop sophisticated machine-learning models to derive valuable insights and predictions from the data. These models may include regression, classification, clustering, and more. Data Warehousing: Amazon Redshift, Google BigQuery, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

The MLOps Blog

JUNE 27, 2023

SageMaker Studio offers built-in algorithms, automated model tuning, and seamless integration with AWS services, making it a powerful platform for developing and deploying machine learning solutions at scale. Metaflow Metaflow helps data scientists and machine learning engineers build, manage, and deploy data science projects.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

The MLOps Blog

JUNE 13, 2024

You should test the entire ML model development chain, for example: Data collection: Test the quality, accuracy, and relevance of the data collected to ensure it meets the needs of the model. Feature creation: Validate and test the processes used to select, manipulate, and transform data.

ML 59

ML ML Data Scientist Azure 59

DagsHub

NOVEMBER 11, 2024

In this article, we’ll explore how AI can transform unstructured data into actionable intelligence, empowering you to make informed decisions, enhance customer experiences, and stay ahead of the competition. What is Unstructured Data? Word2Vec , GloVe , and BERT are good sources of embedding generation for textual data.

AI 52

AI AI Data Lakes Database 52

DagsHub

OCTOBER 28, 2024

LLM Gateways can enforce security policies, encrypt sensitive information, and manage access control to protect data. They act as a security layer, adding an extra level of protection when handling sensitive data. Model and Cloud Agnosticism Many LLM Gateways are designed to be model and cloud-agnostic.

ML 52

ML ML AWS AI 52

DagsHub

OCTOBER 23, 2024

NoSQL Databases NoSQL databases do not follow the traditional relational database structure, which makes them ideal for storing unstructured data. They allow flexible data models such as document, key-value, and wide-column formats, which are well-suited for large-scale data management.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

The MLOps Blog

JANUARY 25, 2023

A multilingual embedding model is an effective tool that combines semantic information for language understanding with the ability to encode text from various languages into a common embedding space. This allows it to be used for a variety of downstream tasks, including text classification, clustering, and others.

Natural Language Processing 52

Natural Language Processing ML ML Deep Learning 52

Hacker News

NOVEMBER 14, 2023

The data from D10 was never actually transferred to D11, meaning the business is now using 2 systems instead of 1. D11 data model doesn’t really support the data in D10 either. Technology teams demanded that BackEnd be built in Microsoft Azure Pipelines, to comply with “Strategic Vision”.

Power BI 125

Power BI Database Algorithm Azure 125

The MLOps Blog

OCTOBER 3, 2023

It’s almost like a specialized data processing and storage solution. For example, you can use BigQuery , AWS , or Azure. It can be a cluster run by Kubernetes or maybe something else. Mikiko Bazeley: Yeah, so we actually did a talk at Data Council. I would need to have the infrastructure to perform computations.

ML 52

ML ML Data Scientist Machine Learning 52