CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. Organization: Columbia University Price: Students pay Columbia Engineering’s rate of tuition (US$2,362 per credit).

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

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.

Deep Learning 67

Deep Learning Experimentation Machine Learning Risk 67

IBM Big Data Hub

MAY 25, 2023

The Center of Excellence (CoE) already has more than 1,000 consultants with specialized generative AI expertise that are engaging with a global set of clients to drive productivity in IT operations and core business processes like HR or marketing, elevate their customer experiences and create new business models.

Consulting 103

Consulting Experimentation Machine Learning Modeling 103

IBM Big Data Hub

DECEMBER 5, 2023

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications.

Unstructured Data 92

Unstructured Data Cost-Benefit Experimentation Machine Learning 92

CIO Business Intelligence

FEBRUARY 21, 2024

One is knowledge of the emerging mega trends in technology — data, AI, and machine learning — and the other is understanding organizational culture needed to advance the technology goals and to inspire contributors,” he says. We developed a model to predict student outcomes based on metrics from historical evidence,” he says. “We

Recreation/Entertainment 134

Recreation/Entertainment Experimentation Modeling Data-driven 134

IBM Big Data Hub

DECEMBER 4, 2023

Advacements in machine learning algorithms, neural networks and the computational power of generative AI, combined with human expertise, intuition and creativity, can unlock new possibilities and achieve levels of innovation that were previously unimaginable.

Experimentation 64

Experimentation Modeling Metrics Machine Learning 64

DataRobot Blog

OCTOBER 18, 2022

Monitoring and Managing AI Projects with Model Observability. Model Observability – the ability to track key health and service metrics for models in production – remains a top priority for AI-enabled organizations. Monitoring with Machine Learning. DataRobot Booth at Big Data & AI Toronto 2022.

Big Data 96

Big Data Forecasting Experimentation Metrics 96

DataRobot

MARCH 10, 2021

In this blog post, I will focus on the use of the word autonomous , the dangers of using it with stakeholders, and, in the context of customer experience, the inaccurate perception that all things can be automated, eliminating the need for interactions between employees and customers. Deploy the machine learning model into production.

Experimentation 145

Experimentation Machine Learning Key Performance Indicator Reporting 145

Corinium

JUNE 6, 2019

Beyond that, we recommend setting up the appropriate data management and engineering framework including infrastructure, harmonization, governance, toolset strategy, automation, and operating model. It is also important to have a strong test and learn culture to encourage rapid experimentation.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

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. Remember that digital transformation is about transforming your business and operating models with technology.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

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 93

Cost-Benefit Modeling Manufacturing Interactive 93

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

DataRobot

SEPTEMBER 22, 2021

You have to pick the right model to meet expected performance goals. You have to know how to take your model into production, manage it over time, enable the business to consume predictions from it, and use it to make the right decisions. You need to understand what data sources to go after and how to get the data ready.

Experimentation 85

Experimentation Testing Modeling Machine Learning 85

DataRobot

JUNE 23, 2021

As they strive to improve models, data scientists continually try new approaches to refine their predictions. To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. Composable ML then lets you add new types of feature engineering or build entirely new models.

Machine Learning 52

Machine Learning Experimentation Modeling Visualization 52

Cloudera

AUGUST 20, 2020

Machine Learning (ML) and Artificial Intelligence (AI), while still emerging technologies inside of enterprise organisations, have given some companies the ability to dynamically change their fortunes and reshape the way they are doing business — that is if they are brave enough to experiment and explore the unknown.

Enterprise 120

Enterprise Experimentation Uncertainty Deep Learning 120

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

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. Capabilities Beyond Classic Jupyter for End-to-end Experimentation.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

Insight

MARCH 12, 2020

The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Features: DistilBERT Text Embeddings Once I had a raw dataset, I could begin engineering features and building a natural language processing (NLP) model.

Modeling 59

Modeling Metadata Publishing Sales 59

Domino Data Lab

AUGUST 5, 2019

As more companies become model-driven , data scientists are uniquely positioned to drive innovation and to help their companies remain economically strong. the model context ) when building and using models enable data scientists to directly impact business problems. data munging, building models, etc.).

Data Science 93

Data Science Data-driven Modeling Machine Learning 93

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

Ontotext

APRIL 3, 2024

W hen you try to automate business processes, semantics, and machine learning , knowledge graphs can bring a lot of value. Nimit Mehta: I think that 2024 is going to be a buckle-down year, but, at the same time, we’ll see a rapid explosion of experimentation. Aurelije Zovko : For me, it is a digital transformation. Maybe later.

Technology 59

Technology Risk Digital Transformation Measurement 59

Occam's Razor

MARCH 23, 2021

The other dimension to consider is most Analtyics teams kick into gear after the campaign is concluded, after the customer interaction has taken place in the call center, and after the funds budgeted have already been spent. That’s not really surprising, if your view of your scope is narrow… Your impact will be narrow as well.

Analytics 131

Analytics Scorecard Strategy Testing 131

Sisense

MARCH 26, 2021

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. But there’s a gap between expectations and reality, and companies are falling short of their aspirations.

Analytics 98

Analytics Data-driven Dashboards Experimentation 98

Domino Data Lab

DECEMBER 4, 2020

NCA doesn’t require the assumption of a specific compartmental model for either drug or metabolite; it is instead assumption-free and therefore easily automated [1]. PharmaceUtical Modeling And Simulation (or PUMAS) is a suite of tools to perform quantitative analytics for pharmaceutical drug development [2]. Mean residence time.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

CIO Business Intelligence

MAY 9, 2024

And because generative AI (genAI) is interactive and dialogue-based, it can help you get into a state of flow. Experimentation drives momentum: How do we maximize the value of a given technology? Via experimentation. Learn how DataStax enables production -ready GenAI applications. AI changes the game.

Enterprise 112

Enterprise Experimentation Sales Optimization 112

CIO Business Intelligence

MAY 1, 2024

Gen AI takes us from single-use models of machine learning (ML) to AI tools that promise to be a platform with uses in many areas, but you still need to validate they’re appropriate for the problems you want solved, and that your users know how to use gen AI effectively.

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

DataRobot Blog

SEPTEMBER 30, 2022

How do you track the integrity of a machine learning model in production? Model Observability can help. By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Model Observability Features.

Slice and Dice 52

Slice and Dice Modeling Metrics Experimentation 52

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

O'Reilly on Data

SEPTEMBER 15, 2020

This in turn would increase the platform’s value for users and thus increase engagement, which would result in more eyes to see and interact with ads, which would mean better ROI on ad spend for customers, which would then achieve the goal of increased revenue and customer retention (for business stakeholders).

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

CIO Business Intelligence

OCTOBER 4, 2022

Customers gravitate to personalized interactions and show a preference for companies that anticipate and cater to their unmet needs. Philips teams across the company use Healthsuite to build ML models that help the company’s healthcare customers unlock data insights, including clinical predictions and operational forecasts.

Data-driven 109

Data-driven Machine Learning Interactive Predictive Analytics 109

DataRobot

SEPTEMBER 14, 2021

As AI continues to advance at such an aggressive pace, solutions built on machine learning are quickly becoming the new norm. And for those that do make it past the experimental stage, it typically takes over 18 months for the value to be realized. Accurate models today become inaccurate tomorrow.

Machine Learning 94

Machine Learning Modeling Experimentation Visualization 94

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

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. hill climbing ) ( Clue #1 ).

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

AWS Big Data

MARCH 20, 2023

Although these batch analytics-based efforts were successful to some extent, they saw opportunities to improve the customer experience with real-time personalization and security guidance during the customer’s interaction with the Poshmark app. User interactions on Poshmark web and mobile applications generate server-side events.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

Corinium

APRIL 25, 2019

I’ve found many IT as well as Business leaders have a mental model of data in that it is simply part of, or belongs to, a specific database or application, and thus they falsely conclude that just procuring a tool to protect that given environment will sufficiently protect that data. This is a much more proactive and scalable model.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. In the present chapter [excerpt], we cover code that will enable you to create your own word vectors as well as to provide them as an input into a deep learning model. A complementary Domino project is available.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Data Science and Beyond

JULY 22, 2018

It’s not all about machine learning. Kaggle was only about predictive modelling competitions back then, and so I believed that data science is about using machine learning to build models and deploy them as part of various applications. But what does it mean? What do I actually do here?

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79