Towards AI

APRIL 27, 2023

Last Updated on May 2, 2023 by Editorial Team Author(s): Puneet Jindal Originally published on Towards AI. garbage in garbage out for AI model accuracy….blah By this time, it's already months or years of efforts that have gone by without concrete results where AI is working at scale with its impact driving the bottom or top line.

Automation 85

Automation Auto-complete Computer Vision ML Engineer 85

AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

Data Science 103

Data Science Data Drift DevOps Auto-complete 103

AWS Machine Learning Blog

MARCH 1, 2023

Continuous ML model retraining is one method to overcome this challenge by relearning from the most recent data. This requires not only well-designed features and ML architecture, but also data preparation and ML pipelines that can automate the retraining process. We define another pipeline step, step_cond.

Automation 84

Automation ETL Data Drift ML 84

AWS Machine Learning Blog

JUNE 13, 2023

This post is co-written with Jad Chamoun, Director of Engineering at Forethought Technologies, Inc. and Salina Wu, Senior ML Engineer at Forethought Technologies, Inc. Forethought is a leading generative AI suite for customer service. The following diagram illustrates our legacy architecture.

Generative AI 63

Generative AI Auto-complete AI Modeling Machine Learning 63

DataRobot Blog

JANUARY 10, 2023

Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. The new DataRobot Notebooks offering plays a crucial role in providing a collaborative environment for AI builders to use a code-first approach to accelerate one of the most time-consuming parts of the machine learning lifecycle.

Auto-classification 52

Auto-classification Auto-complete Data Scientist Data Science 52

Flipboard

MARCH 13, 2023

With terabytes of data generated by the product, the security analytics team focuses on building machine learning (ML) solutions to surface critical attacks and spotlight emerging threats from noise. These endpoints are fully managed, load balanced, and auto scaled, and can be deployed across multiple Availability Zones for high availability.

Data Scientist 102

Data Scientist Auto-complete ML Machine Learning 102

The MLOps Blog

JUNE 27, 2023

This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. They should also offer version control capabilities to manage the changes and revisions of ML artifacts, ensuring reproducibility and facilitating effective teamwork.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134