Domino Data Lab

AUGUST 6, 2021

When you factor in the requirements of a business-critical machine learning model in a working enterprise environment, the old cat-herding meme won’t even get a smile. Develop: includes accessing and preparing data and algorithms, researching and development of models and experimentation. 4 Steps in the DSLC.

Data Science 75

Data Science Testing Modeling Publishing 75

DataRobot

APRIL 19, 2021

Most modern artificial intelligence systems are powered by machine learning algorithms , which learn by example. Data scientists train the algorithms using datasets that contain curated learning examples. The model was worthless. After the initial shock and disappointment, I reviewed my work.

Machine Learning 52

Machine Learning Visualization Data-driven Data Science 52

CIO Business Intelligence

JUNE 28, 2023

Even among the companies permitting the tools, many are publishing stringent usage guidelines, and are proactively working with technology partners to accelerate access to enterprise-grade solutions with more robust security. Experimentation with a use case driven approach. Business fundamentals still apply.

Enterprise 52

Enterprise Experimentation Risk Data-driven 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

Cloudera

APRIL 13, 2021

You’ve probably heard it more than once: Machine learning (ML) can take your digital transformation to another level. Unfortunately, most organizations run into trouble when it comes to bridging the gap that exists between experimentation and full-scale ML production. It’s a pie-in-the-sky statement that sounds great, right?

Machine Learning 97

Machine Learning Enterprise Experimentation Modeling 97

Insight

MARCH 27, 2019

The main benefits and features of DeepAugment are: Reduces the error rate of CNN models (showed 60% decrease in error for CIFAR10 on WRN-28–10) Saves time by automating the process 50 times faster than Google’s previous solution– AutoAugment The finished package is on PyPI. To learn more about how I built this, read on!

Optimization 75

Optimization Cost-Benefit Modeling Strategy 75

Sisense

MARCH 26, 2021

Newly published research shows that companies aren’t getting the most out of their analytics. Companies surveyed by Harvard Business Review Analytic Services (HBR) report that two of the most important strategic benefits of using data analytics are (1) identifying new revenue and business models and (2) becoming more innovative.

Analytics 98

Analytics Data-driven Dashboards Experimentation 98

DataRobot Blog

MARCH 16, 2023

release, we’ve made it easy for you to rapidly prepare data, engineer new features and subsequently automate model deployment and monitoring into your Snowflake data landscape, all with limited data movement. We’ve tightened the loop between ML data prep , experimentation and testing all the way through to putting models into production.

Modeling 52

Modeling Experimentation Machine Learning Data-driven 52

Rocket-Powered Data Science

JULY 6, 2021

2) MLOps became the expected norm in machine learning and data science projects. 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.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

AWS Big Data

OCTOBER 4, 2023

Use business terms to search, share, and access cataloged data, making data accessible to all the configured users to learn more about data they want to use with the business glossary. Automate data discovery and cataloging with machine learning (ML). In this release, Amazon DataZone introduces a new data model for the catalog.

Metadata 100

Metadata Data Lake Publishing Data Governance 100

Insight

FEBRUARY 20, 2020

Only Bias Understanding why noise in machine learning is nothing but bias In this post, we explain how bias and noise in machine learning are two sides of the same coin. Read on to see how the same goes for the fundamental laws of machine learning. There is No Noise?—?Only God does not play dice.?—?Albert

Machine Learning 71

Machine Learning Experimentation Modeling Measurement 71

Domino Data Lab

FEBRUARY 4, 2019

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Ensure a culture that supports a steady process of learning and experimentation. This is not that.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. 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.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Data Science and Beyond

JULY 22, 2018

Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics. It’s not all about machine learning. 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

DataRobot Blog

FEBRUARY 15, 2023

In addition, it’s essential that models comply with regulations and treat customers fairly, making it more important than ever to monitor models in production. We also look at how collaboration is built into the core of the DataRobot AI platform so that your entire team can collaborate from business use case to model deployment.

Modeling 52

Modeling Machine Learning Cost-Benefit Metrics 52

Domino Data Lab

JULY 28, 2021

For companies creating models to scale, an enterprise Machine Learning Operation (MLOps) platform not only needs to support enterprise-grade development and production, it needs to follow the same standard process that data scientists use. Develop Stage. Deploy Stage.

Data Science 59

Data Science Enterprise Modeling Experimentation 59

AWS Big Data

JULY 26, 2023

The vector engine provides a simple, scalable, and high-performing similarity search capability in Amazon OpenSearch Serverless that makes it easy for you to build modern machine learning (ML) augmented search experiences and generative artificial intelligence (AI) applications without having to manage the underlying vector database infrastructure.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

Cloudera

NOVEMBER 25, 2020

As Augmented Analytics is on the rise, a discovery data warehouse is key for not only pharmaceuticals but any businesses that heavily rely on unstructured data, such as healthcare providers, insurance, government, media, various ML and Risk modeling heavy organizations, as well as legal/law enforcement and a variety of auditing services.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. An ML-related topic, “models,” was No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

CIO Business Intelligence

APRIL 15, 2024

Tax preparation company H&R Block is no stranger to AI and machine learning (ML), having leveraged the technologies across its business for years. Given the speed required, Lowden established a specialized team for the project to encourage a culture of experimentation and “moving fast to learn fast.” “You

Testing 74

Testing Experimentation Data Quality Machine Learning 74

Cloudera

MAY 31, 2023

Riding the wave of the generative AI revolution, third party large language model (LLM) services like ChatGPT and Bard have swiftly emerged as the talk of the town, converting AI skeptics to evangelists and transforming the way we interact with technology. Adding Enterprise Context to LLMs Contextual Limitation is not unique to enterprises.

Enterprise 73

Enterprise Data Processing Experimentation Modeling 73

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. The first two are from editions of my newsletter, The Marketing – Analytics Intersect (it goes out weekly, and is now my primary publishing channel, sign up!). Deep Learning.

Marketing 136

Marketing Analytics Machine Learning Strategy 136

O'Reilly on Data

MAY 11, 2020

Not all models are created equal, however: they operate on different principles, and impact us as individuals and communities in different ways. To understand the menagerie of models that are fundamentally altering our individual and shared realities, we need to build a typology, a classification of their effects and impacts.

Modeling 190

Modeling Advertising Recreation/Entertainment Metrics 190