DataKitchen

APRIL 13, 2021

Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. . To date, we count over 100 companies in the DataOps ecosystem. However, the rush to rebrand existing products with a DataOps message has created some marketplace confusion. Meta-Orchestration . Soda Data Monitoring — Soda tells you which data is worth fixing.

Testing 304

Testing Machine Learning Consulting Data Science 304

Cloudera

JULY 27, 2021

Here in the virtual Fast Forward Lab at Cloudera , we do a lot of experimentation to support our applied machine learning research, and Cloudera Machine Learning product development. We believe the best way to learn what a technology is capable of is to build things with it.

Data Science 117

Data Science Enterprise Experimentation Machine Learning 117

CIO Business Intelligence

FEBRUARY 22, 2024

With the aim to accelerate innovation and transform its digital infrastructures and services, Ferrovial created its Digital Hub to serve as a meeting point where research and experimentation with digital strategies could, for example, provide new sources of income and improve company operations.

IT 105

IT Digital Transformation IoT Cost-Benefit 105

CIO Business Intelligence

OCTOBER 3, 2024

Rather than pull away from big iron in the AI era, Big Blue is leaning into it, with plans in 2025 to release its next-generation Z mainframe , with a Telum II processor and Spyre AI Accelerator Card, positioned to run large language models (LLMs) and machine learning models for fraud detection and other use cases. At least IBM believes so.

Machine Learning 140

Machine Learning Experimentation Insurance Modeling 140

CIO Business Intelligence

AUGUST 15, 2024

The inflated expectations were so inflated from the early days and have kept on, and I think this is going to be a pretty deep trough of disillusionment,” says Chris Stephenson, managing director of intelligent automation, AI, and digital services at IT consulting firm alliantgroup, affirming Gartner’s hype cycle.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

CIO Business Intelligence

APRIL 25, 2023

A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. GPT stands for generative pre-trained transformer. Five years later, transformer architecture has evolved to create powerful models such as ChatGPT. It was 2 years from GPT-2 (February 2019) to GPT-3 (May 2020), 2.5

Experimentation 116

Experimentation Deep Learning Enterprise Modeling 116

Domino Data Lab

OCTOBER 14, 2020

Experimentation and collaboration are built into the core of the platform. We needed an “evolvable architecture” which would work with the next deep learning framework or compute platform. This ability enhances the efficiency of operational management and optimizes the cost of experimentation. Why Sagemaker?

Experimentation 99

Experimentation Deep Learning Modeling Testing 99

Domino Data Lab

APRIL 7, 2019

A good NLP library will, for example, correctly transform free text sentences into structured features (like cost per hour and is diabetic ), that easily feed into a machine learning (ML) or deep learning (DL) pipeline (like predict monthly cost and classify high risk patients ). per hour” doesn’t start a new sentence.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

CIO Business Intelligence

MAY 23, 2022

The traditional approach for artificial intelligence (AI) and deep learning projects has been to deploy them in the cloud. For many nascent AI projects in the prototyping and experimentation phase, the cloud works just fine. Hybrid is a perfect fit for some AI projects. Cloud Architecture, IT Leadership

Cost-Benefit 98

Cost-Benefit Experimentation Data Lake Deep Learning 98

Domino Data Lab

FEBRUARY 12, 2020

for reinforcement learning (RL), ? for model serving (experimental), are implemented with Ray internally for its scalable, distributed computing and state management benefits, while providing a domain-specific API for the purposes they serve. Motivations for Ray: Training a Reinforcement Learning (RL) Model. by adding the ?@ray.remote?

Experimentation 137

Experimentation Modeling Data Science Machine Learning 137

Cloudera

AUGUST 20, 2020

UOB used deep learning to improve detection of procurement fraud, thereby fighting financial crime. Acceptance that it will be an experiment — ML really requires a lot of experimentation, and often times you don’t know what’s going to be successful. But UOB didn’t stop there. It’s about how you approach AI and ML.

Enterprise 121

Enterprise Experimentation Uncertainty Deep Learning 121

CIO Business Intelligence

JANUARY 19, 2024

You should also have experience with pattern detection, experimentation in business optimization techniques, and time-series forecasting. and SAS Text Analytics, Time Series, Experimentation, and Optimization. The exam tests your knowledge of and ability to integrate machine learning into various tools and applications.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

Smart Data Collective

DECEMBER 24, 2020

Machine learning is the driving force of AI. It allows humans to essentially teach software in a matter of weeks what a human would take decades to learn. AI and machine learning are changing the world we live in and altering the way we do things. This demonstrates the limitations of machine learning.

Machine Learning 121

Machine Learning Experimentation Software Reporting 121

DataRobot

DECEMBER 16, 2021

Take advantage of DataRobot’s wide range of options for experimentation. Allow the platform to handle infrastructure and deep learning techniques so that you can maximize your focus on bringing value to your organization. Taking Text AI to the Next Level. An estimated 80% of all organizational information is held in text.

Unstructured Data 98

Unstructured Data Experimentation Deep Learning Modeling 98

IBM Big Data Hub

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions. Morgan’s Athena uses Python-based open-source AI to innovate risk management.

Deep Learning 64

Deep Learning Experimentation Machine Learning Risk 64

FineReport

DECEMBER 19, 2019

For the super rookie, the learning cost and threshold are relatively low, and it is easy to get started. If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you.

Knowledge Discovery 98

Knowledge Discovery Visualization Data mining Reporting 98

CIO Business Intelligence

AUGUST 21, 2024

The flashpoint moment is that rather than being based on rules, statistics, and thresholds, now these systems are being imbued with the power of deep learning and deep reinforcement learning brought about by neural networks,” Mattmann says. According to Gartner, an agent doesn’t have to be an AI model.

Risk 136

Risk Insurance Cost-Benefit Software 136

Domino Data Lab

JULY 2, 2019

Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Here’s a sampler of related papers and articles if you’d like to dig in further: “ Synthesizing Programs with Deep Learning ” – Nishant Sinha (2017-03-25). “ Program Synthesis. Done and done.

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

IBM Big Data Hub

DECEMBER 5, 2023

According to IBM’s latest CEO study , industry leaders are increasingly focusing on AI technologies to drive revenue growth, with 42% of retail CEOs surveyed banking on AI technologies like generative AI, deep learning, and machine learning to deliver results over the next three years.

Unstructured Data 90

Unstructured Data Cost-Benefit Machine Learning Experimentation 90

Dataiku

MARCH 25, 2024

By leveraging advanced deep learning architectures, M-LLMs can analyze the image and question simultaneously, extracting relevant features from both modalities and synthesizing them into a cohesive understanding. Intrigued, you type in a question about the location, expecting a response from a fellow user.

Visualization 132

Visualization Modeling Experimentation Testing 132

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

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. Automated development: With AutoAI , beginners can quickly get started and more advanced data scientists can accelerate experimentation in AI development.

Machine Learning 71

Machine Learning Manufacturing Deep Learning Cost-Benefit 71

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. AI Platform Single-Tenant SaaS are fully managed by DataRobot and replace disparate machine learning tools, simplifying management.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

CDW Research Hub

AUGUST 21, 2019

Finally, perhaps the biggest obstacle faced when adopting an AI project is the time it takes to configure the server, prepare the data, build and train the model, and deploy and infer for deep learning. The kit helps facilitate clients’ AI adoption journey from experimentation to production. Other AI Starte r Kit Features.

Strategy 45

Strategy Deep Learning Machine Learning Experimentation 45

IBM Big Data Hub

MARCH 27, 2024

The experimental results indicate that fine-tuned LLMs exhibit significant improvements over the zero-shot classification approach. Here’s where deep learning-based foundation models for NLP can be efficient across a broad range of NLP classification tasks when availability of labelled data is insufficient or limited.

Experimentation 73

Experimentation Deep Learning Modeling Data-driven 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. They never had to worry that they have to be in a persistent forward motion… sometimes just to stay current. This reality powers my impostor syndrome, and (yet?) This is normal.

Marketing 138

Marketing Analytics Machine Learning Strategy 138

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI. classification problem.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

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 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. They talk about AI without really seeming to know what it is.”

Sales 52

Sales Machine Learning Experimentation Deep Learning 52

Ontotext

NOVEMBER 6, 2019

At the same time, the community there is of users can share the best practices, enabling the cross-pollination of the most successful and most fruitful results of their experimentation. The release of a new full version always comes with an exciting list of new functionalities. Version 9.0 What does it mean for GraphDB clients?

Experimentation 45

Experimentation Deep Learning Software Modeling 45

IBM Big Data Hub

APRIL 18, 2024

AGI, sometimes referred to as strong AI , is the science-fiction version of artificial intelligence (AI), where artificial machine intelligence achieves human-level learning, perception and cognitive flexibility. Imagine a self-driving car piloted by an AGI. It might suggest a restaurant based on preferences and current popularity.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. If you’re an AI product manager (or about to become one), that’s what you’re signing up for. Identifying the problem. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about.

Marketing 364

Marketing Experimentation Metrics Testing 364

O'Reilly on Data

MARCH 19, 2020

O’Reilly online learning is a trove of information about the trends, topics, and issues tech leaders need to know about to do their jobs. Our analysis of ML- and AI-related data from the O’Reilly online learning platform indicates: Unsupervised learning surged in 2019, with usage up by 172%. that support unsupervised learning.

Deep Learning 357

Deep Learning Machine Learning Data-driven Modeling 357

O'Reilly on Data

APRIL 19, 2021

After eliminating 1,580 respondents who didn’t complete the survey, we’re left with 3,574 responses—almost three times as many as last year. It’s possible that pandemic-induced boredom led more people to respond, but we doubt it. Whether they’re putting products into production or just kicking the tires, more people are using AI than ever before.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

Data Science and Beyond

DECEMBER 23, 2018

In my opinion it’s more exciting and relevant to everyday life than more hyped data science areas like deep learning. However, I’ve found it hard to apply what I’ve learned about causal inference to my work. I’ve been interested in the area of causal inference in the past few years.

Deep Learning 103

Deep Learning Experimentation Data Science Data-driven 103

CIO Business Intelligence

MAY 14, 2024

The ML models include classic ML and deep learning to predict category labels from the narrative text in reports. The IT department also used the Hugging Face online AI service and PyTorch, a Python framework for building deep learning models. Azure Databricks is also employed for data analytics as part of the solution.

Machine Learning 97

Machine Learning Deep Learning Reporting Experimentation 97

O'Reilly on Data

SEPTEMBER 11, 2019

Deep learning,” for example, fell year over year to No. Spark has emerged as the general-purpose data processing engine of choice; interest in Hadoop is waning, although reports of its death are greatly exaggerated. We focused this list on important industry terms and terms showing notable year-over-year changes. 221) to 2019 (No.

IoT 26

IoT Big Data Data Warehouse Uncertainty 26

Domino Data Lab

MAY 8, 2019

The same execs who stress needs for ML model interpretability are often the ones who overemphasize the engineering aspects of machine learning, ignoring the social context, in ways that make model interpretability nearly impossible. They’ve become “embedded institutions” in engineering. Businesses would be wise to adapt their views as well.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105