ODSC - Open Data Science

OCTOBER 15, 2023

Elementl / Dagster Labs Elementl and Dagster Labs are both companies that provide platforms for building and managing data pipelines. Elementl’s platform is designed for data engineers, while Dagster Labs’ platform is designed for data scientists. However, there are some critical differences between the two companies.

Machine Learning 52

Machine Learning Machine Learning Data Pipeline AI 52

Dataconomy

AUGUST 22, 2024

We developed a custom data pipeline to handle the immense volume of visual data, resulting in significant cost savings and reduced human exposure to hazardous environments. One of the most promising trends in Computer Vision is Self-Supervised Learning.

ML 91

ML ML Machine Learning Machine Learning 91

IBM Journey to AI blog

AUGUST 11, 2023

Once defined, ML engineers can begin building the ML data pipeline: Create and execute the decision process—Data science teams work with software developers to create algorithms that can process data, search for patterns and “guess” what might come next. How MLOps will be used within the organization.

Data Science 68

Data Science Machine Learning Machine Learning ML 68

ODSC - Open Data Science

SEPTEMBER 20, 2023

Human Centered AI Capturing CAP in a Kappa Data Architecture A Semi-Supervised Anomaly Detection System Through Ensemble Stacking Algorithm Data Science Applied to Manufacturing Problems Building a Data-Driven Workforce AI and Video Games: The Evolution Data Morph: A Cautionary Tale of Summary Statistics Understanding the Landscape of Large Models (..)

Data Wrangling 52

Data Wrangling Data Science Machine Learning Machine Learning 52

DagsHub

DECEMBER 23, 2024

Libact : It is a Python package for active learning. It provides implementations of various active learning algorithms like uncertainty sampling, query-by-committee, and density-weighted methods.   Integrates well with scikit-learn and can be used with any supervised learning model.

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Clustering 52

The MLOps Blog

MARCH 21, 2023

You don’t need a bigger boat : The repository curated by Jacopo Tagliabue shows how several (mostly open-source) tools can be effectively combined together to run data pipelines at scale with very small teams. Solution Data lakes and warehouses are the two key components of any data pipeline.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69

Kaggle

JULY 29, 2020

David: My technical background is in ETL, data extraction, data engineering and data analytics. I spent over a decade of my career developing large-scale data pipelines to transform both structured and unstructured data into formats that can be utilized in downstream systems.

ETL 71

ETL Data Scientist Data Science Machine Learning 71