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. Despite the complexity, mission-critical analytics must be delivered error-free under intense deadline pressure. Requirements continually change.

Experimentation 130

Experimentation Data Lake Marketing Predictive Modeling 130

Smarten

DECEMBER 15, 2017

One very important capability is Put n’ Play predictive analysis. Assisted Predictive Modeling and predictive analysis tools should include sophisticated functionality in a simple environment that is easy for every business user.

Predictive Analytics 63

Predictive Analytics Analytics Predictive Modeling Experimentation 63

Data Science and Beyond

SEPTEMBER 19, 2016

Some people equate predictive modelling with data science, thinking that mastering various machine learning techniques is the key that unlocks the mysteries of the field. However, there is much more to data science than the What and How of predictive modelling. Causality and experimentation.

Data Science 66

Data Science Predictive Modeling Experimentation Deep Learning 66

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. ICSs can reduce the time taken to build population health registries and predictive models by up to 90 percent.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

O'Reilly on Data

SEPTEMBER 15, 2020

Results are typically achieved through a scientific process of discovery, exploration, and experimentation, and these processes are not always predictable. In an early stage of AI maturity, we can build AI solutions that reduce search friction (e.g., automated retirement portfolio rebalancing and maximized ROI).

Cost-Benefit 290

Cost-Benefit Advertising ROI Machine Learning 290

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

DataRobot

JANUARY 13, 2022

To move from experimental AI to production-level, trustworthy, and ROI-driven AI, it’s vital to align data scientists, business analysts, domain experts, and business leaders to leverage overlapping expertise from these groups. It’s easy to deploy, monitor, and manage models in production and react to changing conditions.

ROI 52

ROI Machine Learning Experimentation Data Science 52

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

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. My understanding of data science at the time was heavily influenced by Kaggle and the tech industry.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

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. For example, by using prediction models, they are able to generate a heatmap to tell drivers where they should place themselves to take advantage of the best demand areas.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Smarten

NOVEMBER 3, 2017

Empowers business users with access to meaningful data to test theories and hypotheses without the assistance of data scientists or IT staff.

Analytics 40

Analytics Visualization Experimentation Cost-Benefit 40

Smarten

JULY 3, 2017

Tools like plug n’ play predictive analysis and smart data visualization ensure data democratization and drastically reduce the time and cost of analysis and experimentation.

Predictive Modeling 40

Predictive Modeling Visualization Business Intelligence Experimentation 40

Cloudera

FEBRUARY 16, 2022

Each time a project is successfully deployed, the trained model is recorded within the Models section of the Projects page. The AMPs framework also supports the promotion of models from the lab into production, a common MLOps task. This might require making batch and individual predictions.

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

DataRobot Blog

JULY 28, 2022

More interesting was the 8th place team’s solution, which used a kalman filter rather than a machine learning model to remove noise, and then added statistical methods to build a robust prediction model, which was extremely simple and powerful.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Domino Data Lab

JANUARY 11, 2021

Once a model has been developed, the model needs to be productionized either via an app, an API or in this case, writing model scores from the prediction model back into Snowflake so that business analyst end users are able to access predictions via their reporting tools.

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Modeling 103

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. So as my tiny gift for you here are five experimentation and testing ideas for you. Rather than create prediction models (with faulty assumptions!) This recession season buy your CEO the gift that keeps giving, a experimentation and testing tool.

Testing 112

Testing Experimentation Risk Optimization 112

AWS Big Data

NOVEMBER 14, 2023

With a combination of low-latency data streaming and analytics, they are able to understand and personalize the user experience via a seamlessly integrated, self-reliant system for experimentation and automated feedback. The probability results are also stored in Amazon S3 to continuously retrain the model in SageMaker.

IoT 55

IoT Data-driven Data Lake Data Strategy 55

O'Reilly on Data

SEPTEMBER 11, 2019

But the database—or, more precisely, the data model —is no longer the sole or, arguably, the primary focus of data engineering. If anything, this focus has shifted to the ML or predictive model. Ironically, this shift is attested by declines in several terms that correspond to (or are synonyms for) data engineering.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Domino Data Lab

AUGUST 22, 2019

GloVe and word2vec differ in their underlying methodology: word2vec uses predictive models, while GloVe is count based. We waved our finger in the air to select 64, so some experimentation and optimization are warranted at your end if you feel like it. Natural Language Processing.] together at Stanford University.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111