O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. I will highlight the results of a recent survey on machine learning adoption, and along the way describe recent trends in data and machine learning (ML) within companies.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

O'Reilly on Data

DECEMBER 10, 2019

We can collect many examples of what we want the program to do and what not to do (examples of correct and incorrect behavior), label them appropriately, and train a model to perform correctly on new inputs. In short, we can use machine learning to automate software development itself. Instead, we can program by example. and Matroid.

Software 329

Software Machine Learning Risk Data-driven 329

Smart Data Collective

FEBRUARY 21, 2021

Deep learning tech is influencing and enhancing many industries, promising to provide insights into key business operations which were not previously possible to unearth. One of the biggest applications of this technology lies with using deep learning to streamline fleet management. Route adjustments made in real time.

Deep Learning 107

Deep Learning Management Cost-Benefit Manufacturing 107

CIO Business Intelligence

NOVEMBER 19, 2024

All industries and modern applications are undergoing rapid transformation powered by advances in accelerated computing, deep learning, and artificial intelligence. You build your model, but the history and context of the data you used are lost, so there is no way to trace your model back to the source.

Management 116

Management Unstructured Data Deep Learning Metadata 116

O'Reilly on Data

FEBRUARY 11, 2019

Recent improvements in tools and technologies has meant that techniques like deep learning are now being used to solve common problems, including forecasting, text mining and language understanding, and personalization. AI and machine learning in the enterprise. Deep Learning. Model lifecycle management.

Big Data 269

Big Data Technology Machine Learning Deep Learning 269

CIO Business Intelligence

AUGUST 21, 2024

According to Gartner, an agent doesn’t have to be an AI model. Starting in 2018, the agency used agents, in the form of Raspberry PI computers running biologically-inspired neural networks and time series models, as the foundation of a cooperative network of sensors. “It Adding smarter AI also adds risk, of course. “At

Risk 136

Risk Insurance Cost-Benefit Software 136

Analytics Vidhya

JANUARY 30, 2024

Introduction Large Language Models (LLMs) have revolutionized the field of natural language processing, enabling machines to generate human-like text and engage in conversations. However, these powerful models are not immune to vulnerabilities.

Risk 318

Risk Modeling Analytics Deep Learning 318

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. On the machine learning side, we are entering what Andrei Karpathy, director of AI at Tesla, dubs the Software 2.0

Machine Learning 364

Machine Learning Statistics Data Quality Data Collection 364

O'Reilly on Data

JUNE 7, 2022

DeepMind’s new model, Gato, has sparked a debate on whether artificial general intelligence (AGI) is nearer–almost at hand–just a matter of scale. Gato is a model that can solve multiple unrelated problems: it can play a large number of different games, label images, chat, operate a robot, and more.

Modeling 364

Modeling Interactive Optimization Deep Learning 364

IBM Big Data Hub

SEPTEMBER 27, 2023

Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles and books, to generate text, translate between languages and write many types of content. All this reduces the risk of a data leak or unauthorized access.

Risk 91

Risk Modeling Cost-Benefit Enterprise 91

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 363

Management Machine Learning Experimentation Metrics 363

Analytics Vidhya

SEPTEMBER 28, 2023

However, many languages face the risk of extinction. Introduction Languages are not just forms of communication but repositories of culture, identity, and heritage. Language revitalization aims to reverse this trend, and Generative AI has emerged as a powerful tool in this endeavor.

Risk 334

Risk Analytics Deep Learning Modeling 334

Domino Data Lab

MARCH 16, 2021

We are at an interesting time in our industry when it comes to validating models – a crossroads of sorts when you think about it. There is an opportunity for practitioners and leaders to make a real difference by championing proper model validation. Explaining how deep neural networks work is hard to do. Saliency Maps.

Modeling 122

Modeling Deep Learning Testing Optimization 122

Corinium

JUNE 6, 2019

Regulations and compliance requirements, especially around pricing, risk selection, etc., Beyond that, we recommend setting up the appropriate data management and engineering framework including infrastructure, harmonization, governance, toolset strategy, automation, and operating model. In addition, the traditional challenges remain.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

DataRobot Blog

MAY 26, 2022

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

Risk 52

Risk Modeling Metrics Business Objectives 52

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. These data models predict outcomes of new data. Programming knowledge is needed for the typical tasks of transforming data, creating graphs, and creating data models. Basics of Machine Learning. Machine learning is the science of building models automatically.

Data Science 133

Data Science Statistics Deep Learning Machine Learning 133

IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 56

Deep Learning Machine Learning Unstructured Data Modeling 56

Domino Data Lab

MARCH 6, 2019

Niels Kasch , cofounder of Miner & Kasch , an AI and Data Science consulting firm, provides insight from a deep learning session that occurred at the Maryland Data Science Conference. Deep Learning on Imagery and Text. Deep Learning on Imagery. Introduction. You can see a complete list of talks see here.

Deep Learning 55

Deep Learning Data Science Machine Learning Data Processing 55

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. 415 million (!)

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

CIO Business Intelligence

AUGUST 15, 2024

Many of those gen AI projects will fail because of poor data quality, inadequate risk controls, unclear business value , or escalating costs , Gartner predicts. When we do planning sessions with our clients, two thirds of the solutions they need don’t necessarily fit the generative AI model.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Models can be designed, for instance, to discover relationships between various behavior factors.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Introduction.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

Domino Data Lab

MARCH 11, 2021

Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and easier. Machine learning is used in almost every industry, notably finance , insurance , healthcare , and marketing. TensorFlow runs on both CPUs and GPUs. Tensorflow 2.0,

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

CIO Business Intelligence

OCTOBER 4, 2023

User data is also housed in this layer, including profile, behavior, transactions, and risk. We’ve been working on this for over a decade, including transformer-based deep learning,” says Shivananda. PayPal’s deep learning models can be trained and put into production in two weeks, and even quicker for simpler algorithms.

Digital Transformation 132

Digital Transformation Deep Learning Data Lake Risk 132

O'Reilly on Data

FEBRUARY 18, 2020

There’s plenty of security risks for business executives, sysadmins, DBAs, developers, etc., Normalized search frequency of top terms on the O’Reilly online learning platform in 2019 (left) and the rate of change for each term (right). to be wary of. Figure 1 (above). Terms that correspond with old-school data engineering—e.g.,

Data-driven 363

Data-driven Software Statistics Marketing 363

Smart Data Collective

JULY 8, 2021

Ever since its emergence at the beginning of the century, building information modeling (BIM) has streamlined the construction process of buildings, up from their conception to execution. These systems will not only improve and accelerate construction projects but also provide even more data to ensure precise building information models.

Cost-Benefit 131

Cost-Benefit Deep Learning Visualization Modeling 131

CIO Business Intelligence

OCTOBER 4, 2023

There’s also strong demand for non-certified security skills, with DevSecOps, security architecture and models, security testing, and threat detection/modelling/management attracting the highest pay premiums.

Prescriptive Analytics 135

Prescriptive Analytics IT Machine Learning Deep Learning 135

IBM Big Data Hub

JUNE 14, 2023

Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. And then you need highly specialized, expensive and difficult to find skills to work the magic of training an AI model. But that’s all changing thanks to pre-trained, open source foundation models.

Modeling 84

Modeling Data Lake Enterprise Deep Learning 84

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 ). Training domain-specific models.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

CIO Business Intelligence

JULY 5, 2023

Artificial intelligence and machine learning are the No. Generative AI is raising the interest level even further as organizations begin testing different use cases for deep-learning models. Chrome, for example, uses ML models to help organizations rapidly identify risky sites.

Machine Learning 98

Machine Learning Deep Learning Enterprise Consulting 98

IBM Big Data Hub

MAY 9, 2023

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. Data must be laboriously collected, curated, and labeled with task-specific annotations to train AI models. We stand on the frontier of an AI revolution.

Enterprise 128

Enterprise Technology Modeling Cost-Benefit 128

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.

Machine Learning 140

Machine Learning Experimentation Insurance Modeling 140

CIO Business Intelligence

OCTOBER 10, 2023

A technology inflection point Generative AI operates on neural networks powered by deep learning systems, just like the brain works. These systems are like the processes of human learning. Large learning models (LLMs) that back these AI tools require storage of that data to intelligently respond to subsequent prompts.

Enterprise 124

Enterprise Deep Learning Interactive Software 124

CIO Business Intelligence

APRIL 15, 2022

Derek Driggs, a machine learning researcher at the University of Cambridge, together with his colleagues, published a paper in Nature Machine Intelligence that explored the use of deep learning models for diagnosing the virus. The algorithm learned to identify children, not high-risk patients.

Analytics 145

Analytics Machine Learning Insurance Testing 145

Laminar Security

DECEMBER 13, 2023

Close to 70% of respondents in an ISC report indicated that they believe their organization lacks requisite cybersecurity staff to handle cloud data risk effectively. Learn in this article how Laminar harnesses AI for data discovery and classification and reduces public cloud data risks.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119