DataRobot Blog

JULY 28, 2022

Companies are emphasizing the accuracy of machine learning models while at the same time focusing on cost reduction, both of which are important. In addition to the accuracy of the models we built, we had to consider business metrics, cost, interpretability, and suitability for ongoing operations. Sensor Data Analysis Examples.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

DataRobot Blog

AUGUST 10, 2022

Snowflake provides a state-of the-art data platform for collating and analysing workforce data, and with the combined addition of DataRobot Solution Accelerator models, trusts can have predictive models running with little experimentation — further accelerated by the wide range of supportive datasets available through the Snowflake Marketplace.

Forecasting 52

Forecasting Experimentation Data-driven Risk 52

Domino Data Lab

JANUARY 11, 2021

Arming data science teams with the access and capabilities needed to establish a two-way flow of information is one critical challenge many organizations face when it comes to unlocking value from their modeling efforts. Domino Data Lab and Snowflake: Better Together. Execute a statement that will generate a result set.

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Modeling 103

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. Capabilities Beyond Classic Jupyter for End-to-end Experimentation. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

Smarten

NOVEMBER 3, 2017

Business users can quickly and easily prepare and analyze data and visualize and explore data, notate and highlight data and share data with others to identify the important ‘nuggets’, buried in traditional data, and to connect the dots, find exceptions, identify patterns and trends and better predict results.

Analytics 40

Analytics Visualization Experimentation Cost-Benefit 40

O'Reilly on Data

SEPTEMBER 15, 2020

In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Outputs from trained AI models include numbers (continuous or discrete), categories or classes (e.g., The Challenge with Defining AI Goals. It also requires buy-in and alignment at the C-level.

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

CIO Business Intelligence

MARCH 5, 2024

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. GitHub first launched its copilot in 2021 , and Microsoft 365 Copilot became generally available a few months ago.

Cost-Benefit 116

Cost-Benefit Advertising Experimentation Software 116

Rocket-Powered Data Science

JULY 6, 2021

MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. the monitoring of very important operational ML characteristics: data drift, concept drift, and model security).

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

DataKitchen

JANUARY 17, 2022

The business analysts creating analytics use the process hub to calculate metrics, segment/filter lists, perform predictive modeling, “what if” analysis and other experimentation. A large pharmaceutical Business Analytics (BA) team struggled to provide timely analytical insight to its business customers. Data is not static.

Experimentation 130

Experimentation Data Lake Marketing Predictive Modeling 130

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Data Science and Beyond

JULY 22, 2018

Kaggle was only about predictive modelling competitions back then, and so I believed that data science is about using machine learning to build models and deploy them as part of various applications. It is now much easier to deploy machine learning models, even without a deep understanding of how they work.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

AWS Big Data

NOVEMBER 14, 2023

With data streaming, you can power data lakes running on Amazon Simple Storage Service (Amazon S3), enrich customer experiences via personalization, improve operational efficiency with predictive maintenance of machinery in your factories, and achieve better insights with more accurate machine learning (ML) models.

IoT 55

IoT Data-driven Data Lake Data Strategy 55

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. And I meant every word of it. I fundamentally believe that is wrong. For a few simple reasons: # 1 It's Not Expensive! You can start for free with a superb tool: Google's Website Optimizer. Look for actionable uniqueness. That is nice, well worth paying for. ]. #

Testing 112

Testing Experimentation Risk Optimization 112

O'Reilly on Data

SEPTEMBER 11, 2019

2 in frequency in proposal topics; a related term, “models,” is No. An ML-related topic, “models,” was No. For example, even though ML and ML-related concepts —a related term, “ML models,” (No. Our analysis of the Strata NY speaker proposals surfaced several notable findings: ML- and AI-related terms predominate.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

DataRobot

JANUARY 20, 2022

. — Collaborating via Snowflake Data Cloud and DataRobot AI Cloud Platform will enable multiple organizations to build a community movement where experimentation, innovation, and creativity flourish. As ICSs mature digitally, there is a need to ensure that all processes, datasets, and models are transparent and are free from bias. –

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

datapine

JANUARY 31, 2022

They’re about having the mindset of an experimenter and being willing to let data guide a company’s decision-making process. The main use of business intelligence is to help business units, managers, top executives, and other operational workers make better-informed decisions backed up with accurate data.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Smarten

JULY 3, 2017

When an enterprise selects a self-serve business intelligence solution with Advanced Data Discovery , Smart Data Visualization , Plug n’ Play Predictive Analysis and Self-Serve Data Preparation , it can create an environment where business users are empowered and become greater assets to the organization. It’s simple!

Predictive Modeling 40

Predictive Modeling Visualization Business Intelligence Experimentation 40