Cloudera

AUGUST 20, 2020

UOB used deep learning to improve detection of procurement fraud, thereby fighting financial crime. Personally, it’s examples such as UOB — ones solving real-world problems and delivering value through data analytics while employing ML and AI — that makes this category really exciting. It’s about how you approach AI and ML.

Enterprise 124

Enterprise Experimentation Uncertainty Deep Learning 124

CIO Business Intelligence

JUNE 12, 2023

It can be about anything from classic data analysis and advanced data analysis, to robotics or machine learning. The vast majority of companies already have a structure for analytics and machine learning, so we’re already there; it doesn’t add much,” she adds. But maybe the next step for salespeople will be to learn it too.”

Sales 52

Sales Machine Learning Experimentation Deep Learning 52

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 90

Cost-Benefit Modeling Manufacturing Interactive 90

FineReport

DECEMBER 19, 2019

For newbies, a tool with low learning difficulty but powerful analytical performance cannot be better. In addition, Jupyter Notebook is also an excellent interactive tool for data analysis and provides a convenient experimental platform for beginners. Reporting of FineReport. Dashboard of FineReport. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Ontotext

NOVEMBER 6, 2019

This new version sees the release of essential plug-ins: data virtualization, a sophisticated ranking of semantic search results, new types of indexing and advanced graph analytics. It is often used by Ontotext clients who have use cases with extreme scalability requirements and a simple data model. The Plugins.

Experimentation 45

Experimentation Deep Learning Software Modeling 45

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. This is critical in our massively data-sharing world and enterprises.

Machine Learning 279

Machine Learning Data-driven IoT Deep Learning 279

O'Reilly on Data

MARCH 18, 2020

Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI. It seems as if the experimental AI projects of 2019 have borne fruit. But what kind? Where AI projects are being used within companies.

Enterprise 307

Enterprise Deep Learning Data Governance Risk 307

DataKitchen

APRIL 13, 2021

Process Analytics. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 300

Testing Machine Learning Consulting Data Quality 300

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. This unified experience optimizes the process of developing and deploying ML models by streamlining workflows for increased efficiency.

Machine Learning 72

Machine Learning Manufacturing Cost-Benefit Deep Learning 72

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. It used deep learning to build an automated question answering system and a knowledge base based on that information.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. Using ML models to search more effectively brought the search space down to 102—which can run on modest hardware. Clearly, SQL helps reduce cognitive load for those who are learning about data management and analytics.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

CDW Research Hub

AUGUST 21, 2019

Some solutions require enough servers to start filling a rack in order to achieve the computer processing needed to create more powerful AI models. Equipped with IBM’s Deep Learning frameworks bundle, Watson Machine Learning Accelerator (WMLA), formerly called PowerAI, the solution is designed for use by 3-5 data scientists.

Strategy 45

Strategy Deep Learning Machine Learning Experimentation 45

O'Reilly on Data

SEPTEMBER 11, 2019

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. Strata attracts the leading names in the fields of data management, data engineering, analytics, ML, and artificial intelligence (AI). The term “ML” is No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. Models trained in DataRobot can also be easily deployed to Azure Machine Learning, allowing users to host models easier in a secure way.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

Domino Data Lab

OCTOBER 14, 2020

Guest post by Jeff Melching, Distinguished Engineer / Chief Architect Data & Analytics. We’ve developed a model-driven software platform, called Climate FieldView , that captures, visualizes, and analyzes a vast array of data for farmers and provides new insight and personalized recommendations to maximize crop yield.

Experimentation 99

Experimentation Modeling Deep Learning Testing 99

O'Reilly on Data

JANUARY 7, 2020

In fact, in our 2019 surveys, more than half of the respondents said AI (deep learning, specifically) will be part of their future projects and products—and a majority of companies are starting to adopt machine learning. To stay competitive, data scientists need to at least dabble in machine and deep learning.

Deep Learning 177

Deep Learning Machine Learning Experimentation Modeling 177

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. Like this blog, it will be particularly relevant for those who are in digital analytics and digital marketing. Analytical Thinking: Skills, Interviewing, Value.

Marketing 136

Marketing Analytics Machine Learning Strategy 136