DataRobot Blog

JULY 28, 2022

Rapid advances in machine learning in recent years have begun to lower the technical hurdles to implementing AI, and various companies have begun to actively use machine learning. The accuracy of machine learning models is highly dependent on the quality of the training data. Sensor Data Analysis Examples.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

CIO Business Intelligence

MARCH 21, 2022

Data scientists are becoming increasingly important in business, as organizations rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies. Data scientist job description. Get the latest insights by signing up for our newsletters. ]

Unstructured Data 137

Unstructured Data Data Analytics Analytics Structured Data 137

Business Over Broadway

MAY 22, 2019

According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT. Also, loyalty leaders infuse analytics into CX programs, including machine learning, data science and data integration.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

DataRobot

JANUARY 13, 2022

Data scientists typically come equipped with skills in three key areas: mathematics and statistics, data science methods, and domain expertise. It offers a visual and intuitive UI that enables anyone to explore and prepare data for machine learning, no matter their previous machine-learning experience.

ROI 52

ROI Machine Learning Experimentation Data Science 52

Occam's Razor

MARCH 23, 2021

A key part of how this manifested in our work was doing truly super-advanced machine-learning powered analysis to answer hard questions that few can successfully. You have the start of a fabulous in-flight optimization engine. This is of course exciting and very cool. More shouting is not really better – and it is expensive!

Analytics 131

Analytics Scorecard Strategy Testing 131

DataRobot

JUNE 8, 2021

Because cluster analysis is an unsupervised algorithm, it does not attempt to select groups that optimize business goals. Modern machine learning algorithms use the exact attributes and historical behavior sequences of individual consumers to predict the next best action you can take that will build their engagement with your brand.

Data-driven 98

Data-driven Testing Marketing Experimentation 98

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. While AGI promises machine autonomy far beyond gen AI, even the most advanced systems still require human expertise to function effectively.

Cost-Benefit 93

Cost-Benefit Modeling Manufacturing Interactive 93

Domino Data Lab

JANUARY 24, 2019

These “automated machine learning” solutions help spread data science work by getting non-expert data scientists in to the model building process, offering drag-and-drop interfaces. This group of solutions targets code-first data scientists who use statistical programming languages and spend their days in computational notebooks (e.g.,

Data Science 65

Data Science Marketing Data-driven Statistics 65

FineReport

DECEMBER 19, 2019

When it comes to data analysis, from database operations, data cleaning, data visualization , to machine learning, batch processing, script writing, model optimization, and deep learning, all these functions can be implemented with Python, and different libraries are provided for you to choose. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. You saw in the previous chapter that conditioning can break statistical dependence. Introduction.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Insight

APRIL 28, 2020

You’ll often see the name “data challenge” used when the take-home assignment involves machine learning or statistics or “coding challenge” when the focus is on evaluating a candidate’s software engineering skills. Length: Highly Variable.

Data-driven 53

Data-driven Data Science Experimentation Measurement 53

Occam's Razor

JULY 24, 2018

The ability to optimize landing pages. The matrix also includes what is likely the world’s first widely available machine learning-powered metric: Session Quality , which you’ll find roughly in the middle. Ignore the metrics produced as an experimental exercise nine months ago.

Analytics 93

Analytics Metrics Strategy Measurement 93

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

MAY 8, 2019

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Not yet, if ever.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Corinium

APRIL 25, 2019

For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. Machine learning can keep up, by continually looking for trends and anomalies, or predictive analytics, that are interesting for the given use case.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Cloudera

NOVEMBER 25, 2020

How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data? Innovate on serviceability and optimize utilization. It would enable faster experimentation with easy, protected, and governed access to a variety of data.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

Domino Data Lab

AUGUST 26, 2019

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. Data scientists, machine learning (ML) researchers, and business stakeholders have a high-stakes investment in the predictive accuracy of models. Introduction.

Testing 79

Testing Modeling Machine Learning Metrics 79

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] Note: In more technical machine learning terms, the cost function of the skip-gram architecture is to maximize the log probability of any possible context word from a corpus given the current target word.] Example 11.6 Example 11.9

Deep Learning 111

Deep Learning Modeling Metrics Testing 111