DataRobot Blog

JUNE 9, 2022

Snowflake Summit 2022 (June 13-16) draws ever closer, and I believe it’s going to be a great event. A couple of sessions I’m excited about include the keynote The Engine & Platform Innovations Running the Data Cloud and learning how the frostbyte team conducts Rapid Prototyping of Industry Solutions. Automated feature discovery.

Data Drift 52

Data Drift Explainability Automation AI 52

ODSC - Open Data Science

OCTOBER 11, 2023

Machine learning models are only as good as the data they are trained on. Even with the most advanced neural network architectures, if the training data is flawed, the model will suffer. Data issues like label errors, outliers, duplicates, data drift, and low-quality examples significantly hamper model performance.

Auto-classification 52

Auto-classification Auto-complete Data Drift Machine Learning 52

AWS Machine Learning Blog

FEBRUARY 27, 2024

In this case, we are developing a forecasting model, so there are two main steps to complete: Train the model to make predictions using historical data. Apply the trained model to make predictions of future events. This is made possible by automating tedious, repetitive MLOps tasks as part of the template.

Machine Learning 106

Machine Learning DevOps Data Quality Data Scientist 106

DataRobot Blog

DECEMBER 15, 2022

This is where the DataRobot AI platform can help automate and accelerate your process from data to value, even in a scalable environment. Let’s run through the process and see exactly how you can go from data to predictions. For example, how holidays and events affect forecasting. Settings for Time Series projects.

Machine Learning 81

Machine Learning AI AI Data Drift 81

AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

Data Drift 94

Data Drift Auto-complete ML Automation 94

The MLOps Blog

JUNE 27, 2023

This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. Automated pipelining and workflow orchestration: Platforms should provide tools for automated pipelining and workflow orchestration, enabling you to define and manage complex ML pipelines.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

The MLOps Blog

MARCH 15, 2023

Automation : Automating as many tasks to reduce human error and increase efficiency. Collaboration : Ensuring that all teams involved in the project, including data scientists, engineers, and operations teams, are working together effectively. But we chose not to go with the same in our deployment due to a couple of reasons.

ETL 52

ETL Data Drift Machine Learning ML 52

AWS Machine Learning Blog

MAY 8, 2024

This meticulous approach allows Dialog Axiata to gain valuable insights into customer behavior, enabling them to predict potential churn events with remarkable accuracy. By conducting experiments within these automated pipelines, significant cost savings could be achieved. Data drift and model drift are also monitored.

ML 88

ML AI AI Categorization 88

AWS Machine Learning Blog

AUGUST 29, 2023

In this post, we describe how to create an MLOps workflow for batch inference that automates job scheduling, model monitoring, retraining, and registration, as well as error handling and notification by using Amazon SageMaker , Amazon EventBridge , AWS Lambda , Amazon Simple Notification Service (Amazon SNS), HashiCorp Terraform, and GitLab CI/CD.

Data Scientist 70

Data Scientist Data Quality Python ML 70

Viso.ai

APRIL 25, 2024

By easily integrating into existing tech stacks, Viso Suite makes it easy to automate inefficient and expensive processes. We provide computer vision models on the edge – where events and activities happen. About us: Viso Suite allows enterprise teams to realize value with computer vision in only 3 days.

Computer Vision 52

Computer Vision Deep Learning Convolutional Neural Networks Python 52

The MLOps Blog

MARCH 28, 2023

The DevOps and Automation Ops departments are under the infrastructure team. This is the phase where they would expose the MVP with automation and structured engineering code put on top of the experiments they run. “We We are using the internal automation tools we already have to make it easy to show our model endpoints.

Machine Learning 59

Machine Learning Automation Data Scientist ML 59

Snorkel AI

JULY 5, 2023

I’ve been a part of projects where we’ve spent an incredible amount of money just trying to collect a small amount of data. But in other cases, as much as you can automate, the better you are. Taking advantage of weak supervision, taking advantage of synthetic data, and data augmentation, all those things can really help.

Large Language Models 52

Large Language Models Metadata AI AI 52

Snorkel AI

JULY 5, 2023

I’ve been a part of projects where we’ve spent an incredible amount of money just trying to collect a small amount of data. But in other cases, as much as you can automate, the better you are. Taking advantage of weak supervision, taking advantage of synthetic data, and data augmentation, all those things can really help.

Large Language Models 52

Large Language Models Metadata AI AI 52