The MLOps Blog

JUNE 27, 2023

With built-in components and integration with Google Cloud services, Vertex AI simplifies the end-to-end machine learning process, making it easier for data science teams to build and deploy models 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

Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Enter a stack name, such as Demo-Redshift. yaml locally.

ML 123

ML ML AWS Data Warehouse 123

ODSC - Open Data Science

APRIL 3, 2023

As the sibling of data science, data analytics is still a hot field that garners significant interest. Companies have plenty of data at their disposal and are looking for people who can make sense of it and make deductions quickly and efficiently.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

DataRobot Blog

OCTOBER 3, 2017

Many announcements at Strata centered on product integrations, with vendors closing the loop and turning tools into solutions, most notably: A Paxata-HDInsight solution demo, where Paxata showcased the general availability of its Adaptive Information Platform for Microsoft Azure.

Data Lakes 52

Data Lakes Azure Data Pipeline Hadoop 52

ODSC - Open Data Science

AUGUST 7, 2023

Databricks Databricks is the developer of Delta Lake, an open-source project that brings reliability to data lakes for machine learning and other cases. Originally posted on OpenDataScience.com Read more data science articles on OpenDataScience.com , including tutorials and guides from beginner to advanced levels!

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Snorkel AI

MARCH 26, 2024

I recently talked with Matt Casey, data science content lead at Snorkel AI, about this case. Reinvestigating the data and updating problematic labels could have taken human labelers several days—perhaps weeks—of cumulative labor. See what Snorkel can do to accelerate your data science and machine learning teams.

Machine Learning 52

Machine Learning Machine Learning Data Lakes Data Science 52

IBM Journey to AI blog

DECEMBER 7, 2023

Automated data preparation and cleansing : AI-powered data preparation tools will automate data cleaning, transformation and normalization, reducing the time and effort required for manual data preparation and improving data quality.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

Snorkel AI

MARCH 26, 2024

I recently talked with Matt Casey, data science content lead at Snorkel AI, about this case. Reinvestigating the data and updating problematic labels could have taken human labelers several days—perhaps weeks—of cumulative labor. Book a demo today. We were ready to help. See what Snorkel option is right for you.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. And so that’s where we got started as a cloud data warehouse.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. And so that’s where we got started as a cloud data warehouse.

SQL 52

SQL ML ML Python 52

The MLOps Blog

MARCH 21, 2023

An ML platform standardizes the technology stack for your data team around best practices to reduce incidental complexities with machine learning and better enable teams across projects and workflows. We ask this during product demos, user and support calls, and on our MLOps LIVE podcast. Why are you building an ML platform?

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69

The MLOps Blog

OCTOBER 20, 2023

Jupyter notebooks have been one of the most controversial tools in the data science community. Nevertheless, many data scientists will agree that they can be really valuable – if used well. I’ll show you best practices for using Jupyter Notebooks for exploratory data analysis.

SQL 52

SQL Database Data Scientist Python 52

Heartbeat

AUGUST 16, 2023

Introduction With the increase in visual data, it can be hard to sort and classify videos, making it difficult for Search Engine Optimization (SEO) algorithms to sort out the video data. YouTube has a vast amount of videos, Instagram reels and TikToks are trending, and OTT platforms have emerged and contributed to the video data lake.

Python 52

Python Deep Learning Deep Learning ML 52

ODSC - Open Data Science

MAY 24, 2023

Building a Business with a Real-Time Analytics Stack, Streaming ML Without a Data Lake, and Google’s PaLM 2 Building a Pizza Delivery Service with a Real-Time Analytics Stack The best businesses react quickly and with informed decisions. Here’s a use case of how you can use a real-time analytics stack to build a pizza delivery service.

Data Lakes 52

Data Lakes ML ML Analytics 52

The MLOps Blog

MAY 9, 2023

The pipelines are interoperable to build a working system: Data (input) pipeline (data acquisition and feature management steps) This pipeline transports raw data from one location to another. Model/training pipeline This pipeline trains one or more models on the training data with preset hyperparameters. Kale v0.7.0.

ML 98

ML ML Machine Learning Machine Learning 98

Flipboard

MAY 15, 2025

Data environments in data-driven organizations are changing to meet the growing demands for analytics , including business intelligence (BI) dashboarding, one-time querying, data science , machine learning (ML), and generative AI. For Project name , enter demo. For Lakehouse catalog name , enter rms-catalog-demo.

AWS 138

AWS SQL Data Lakes Data Warehouse 138