IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

Data Science 58

Data Science Machine Learning Cost-Benefit Deep Learning 58

CIO Business Intelligence

OCTOBER 25, 2023

From IT, to finance, marketing, engineering, and more, AI advances are causing enterprises to re-evaluate their traditional approaches to unlock the transformative potential of AI. What can enterprises learn from these trends, and what future enterprise developments can we expect around generative AI?

Enterprise 133

Enterprise Risk Manufacturing Finance 133

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Rocket-Powered Data Science

DECEMBER 16, 2018

The above example (clustering) is taken from unsupervised machine learning (where there are no labels on the training data). There are also examples of cold start in supervised machine learning (where you do have class labels on the training data). This is the meta-learning phase.

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

CIO Business Intelligence

FEBRUARY 21, 2024

Generative AI (GenAI) continues to amaze users with its ability to synthesize vast amounts of information to produce near-instant outputs. When to choose Knowledge Graphs vs. Vector DBs Specific use cases where Vector DBs excel are in RAG systems designed to assist customer service representatives.

Insurance 64

Insurance Unstructured Data Data Architecture Technology 64

CIO Business Intelligence

APRIL 22, 2022

Data science is a method for gleaning insights from structured and unstructured data using approaches ranging from statistical analysis to machine learning. Data science vs. data analytics. A PhD proves a candidate is capable of doing deep research on a topic and disseminating information to others.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

Rita Sallam

JUNE 2, 2023

The first featured analytics and BI platform Gartner Magic Quadrant leaders while the other showcased high interest data science and machine learning platforms. Here is the link to Alteryx’s Data Science and Machine Learning Bake-Off video. In 2000, the Netherlands had 8.5

Optimization 52

Optimization Insurance Machine Learning Risk 52

Rita Sallam

APRIL 2, 2023

The first featured analytics and BI platform Gartner Magic Quadrant leaders while the other showcased high interest data science and machine learning platforms. Here is the link to Alteryx’s Data Science and Machine Learning Bake-Off video. We did two Bake-Offs this year. In 2000, the Netherlands had 8.5

Optimization 52

Optimization Machine Learning Insurance Risk 52

Cloudera

NOVEMBER 15, 2021

If you’ve ever wondered how much data there is in the world, what types there are and what that means for AI and businesses, then keep reading! Here we mostly focus on structured vs unstructured data. Now let’s explore some of the challenges that copious amounts of data bring to the AI, business, and engineering communities.

Unstructured Data 85

Unstructured Data Recreation/Entertainment Structured Data Reporting 85

Sisense

MAY 27, 2019

Digging Deep For Data Diamonds – The Data Engineer. Using analytics programs, machine learning and other methods, the data scientist designs algorithms to collect, clean, manipulate, organize and analyze data in order to reveal insights that will be useful for their business or stakeholders. Data’s like diamonds.

Statistics 75

Statistics Machine Learning Visualization Big Data 75

Domino Data Lab

FEBRUARY 10, 2019

This blog post provides insights into why machine learning teams have challenges with managing machine learning projects. Why are Machine Learning Projects so Hard to Manage? I’ve watched lots of companies attempt to deploy machine learning?—?some Why is this?

Machine Learning 63

Machine Learning Modeling Deep Learning Metrics 63

DataRobot Blog

FEBRUARY 14, 2022

In the past decade, we’ve seen an explosion in the usage of AI. From predicting which customers are likely to churn to forecasting inventory demand, businesses are adopting AI more and more frequently. With any AI solution , you want it to be accurate. Learn More About Explainable AI. Learn more.

Machine Learning 52

Machine Learning Metrics Sales Modeling 52

Insight

MAY 7, 2019

Transfer learning has simplified image classification tasks. For image classification tasks, transfer learning has proven to be very effective in providing good accuracy with fewer labeled datasets. Transfer learning is a technique that enables the transfer of knowledge learned from one dataset to another.

Modeling 75

Modeling Testing Machine Learning Interactive 75

O'Reilly on Data

JUNE 7, 2022

Not so many years ago, one problem with AI was that AI systems were only good at one thing. After IBM’s Deep Blue defeated Garry Kasparov in chess, it was easy to say “But the ability to play chess isn’t really what we mean by intelligence.” I could presumably learn to play other games, but I don’t have to learn them all.

Modeling 363

Modeling Interactive Optimization Deep Learning 363

Insight

MARCH 5, 2019

Internet of Thing (AWS IoT) Are you looking to transition into the field of machine learning in Silicon Valley, New York, or Toronto? Apply for the upcoming June session today ( Deadline is March 25th for SV and NYC ) or learn more about the Artificial Intelligence program at Insight!

Machine Learning 71

Machine Learning Internet of Things Recreation/Entertainment IoT 71

Analytics Vidhya

JULY 7, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Difference between AI, ML, and DL Everyone wants to become a. The post AI VS ML VS DL-Let’s Understand The Difference appeared first on Analytics Vidhya.

Data Science 270

Data Science Publishing Analytics Deep Learning 270

O'Reilly on Data

OCTOBER 13, 2020

The field of AI product management continues to gain momentum. As the AI product management role advances in maturity, more and more information and advice has become available. One area that has received less attention is the role of an AI product manager after the product is deployed. Debugging AI Products.

Management 244

Management Metrics Machine Learning Modeling 244

DataRobot Blog

APRIL 22, 2022

In our previous post , we talked about how red AI means adding computational power to “buy” more accurate models in machine learning , and especially in deep learning. In their paper, Green AI , Schwarz et al give an equation that explains the variability in resource cost to build models. Conclusion.

Machine Learning 98

Machine Learning Measurement Deep Learning Manufacturing 98

Sisense

AUGUST 6, 2020

In Augmented Apps , we examine how product teams are exploring AI and ML to make their products more intuitive and enhance the user experience. AI and machine learning (ML) are not just catchy buzzwords; they’re vital to the future of our planet and your business. Improving performance with AI.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

CIO Business Intelligence

JUNE 29, 2022

Others see RPA as a stopgap en route to intelligent automation (IA) via machine learning (ML) and artificial intelligence (AI) tools, which can be trained to make judgments about future outputs. Bots are typically low-cost and easy to implement, requiring no custom software or deep systems integration.

Cost-Benefit 145

Cost-Benefit Software Enterprise Machine Learning 145

Occam's Razor

AUGUST 28, 2017

Over the last couple years, I’ve spent an increasing amount of time diving into the possibilities Deep Learning (DL) offers in terms of what we can do with Artificial Intelligence (AI). Through it all, I’ve felt there are a handful of breath-taking realities that most people are not grasping when it comes to an AI-Powered world.

Deep Learning 139

Deep Learning Machine Learning Marketing Strategy 139

IBM Big Data Hub

FEBRUARY 6, 2024

There would be no e-commerce, remote work capabilities or the IT infrastructure framework needed to support emerging technologies like generative AI and quantum computing. Digital transformation: Leverage vast amounts of compute to process big data and harness the latest technologies like generative AI and machine learning (ML).

Cost-Benefit 109

Cost-Benefit Digital Transformation Software Modeling 109

Domino Data Lab

JULY 2, 2019

Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively? The authors of AutoPandas observed that: The APIs for popular data science packages tend to have relatively steep learning curves. That’s the gist of program synthesis. Software writes Software?

Metadata 105

Metadata Machine Learning Data Science Data-driven 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. and dig into details about where science meets rhetoric in data science. Modernists and structuralists beware. I got this.”.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Alation

JANUARY 25, 2022

In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. Using this diagram as our guide, this blog will deep-dive into each layer of the data fabric, starting with the data catalog. What can we learn from these hidden systems? Who uses what asset when?

Metadata 52

Metadata IT Metrics Data-driven 52

Andrew White

JANUARY 9, 2022

Which trends do you see for 2022 in AI & ML technology and tools and tool capabilities? – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. I would take a look at our Top Trends for Data and Analytics 2021 for additional AI, ML and related trends.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Domino Data Lab

SEPTEMBER 18, 2019

This post covers data exploration using machine learning and interactive plotting. As Domino seeks to help data scientists accelerate their work, we reached out to AWP Pearson for permission to excerpt the chapter “Real Estate” from the book, Pragmatic AI: An Introduction to Cloud-Based Machine Learning by Noah Gift.

Visualization 99

Visualization Interactive Machine Learning Data Science 99

Insight

MARCH 20, 2020

How can we use AI to transform this tedious technical exercise into a simple and natural interaction between the computer and designer? Drawbacks: The model learns to generate highly realistic shapes but the annotations are very dense and intensive to create, requiring deep, manually annotated part trees for every model.

Interactive 143

Interactive Modeling Machine Learning Testing 143

O'Reilly on Data

APRIL 2, 2019

Why companies are turning to specialized machine learning tools like MLflow. A few years ago, we started publishing articles (see “Related resources” at the end of this post) on the challenges facing data teams as they start taking on more machine learning (ML) projects. Image by Matei Zaharia; used with permission.

Machine Learning 203

Machine Learning Modeling Data Science Software 203

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

FineReport

APRIL 3, 2024

Key Features of BI Dashboards: Customizable interface Interactivity Real-time data accessibility Web browser compatibility Predefined templates Collaborative sharing capabilities BI Dashboards vs. BI Reports: While both dashboards and reports are pivotal in business intelligence, they serve distinct purposes.

Dashboards 52

Dashboards Visualization Metrics Interactive 52

Andrew White

JANUARY 11, 2021

I am sorry but this is a deep question. The work of data science is more tied to machine learning and so AI and those projects do not focus only on analysis but also automation. What are the new trends around the Data solution architecture (centralized vs de-centralized?). Is that a pathway to succeed?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

OCTOBER 25, 2023

Every day, more companies unlock the potential of artificial intelligence (AI) and machine learning. When AI and machine learning are utilized in embedded analytics, the results are impressive. It uses past data, machine learning, and smart AI to forecast what’s coming down the road.

Analytics 52

Analytics Predictive Analytics Machine Learning Software 52

Occam's Razor

OCTOBER 12, 2017

The Now Career Plan: Analytics Experience vs. Analytical Thinking. The Next Career Plan: Prepping For An AI-First World. The Now Career Plan: Analytics Experience vs. Analytical Thinking. There is always more you can learn. There are so many lessons to be learned. I learned a lot. It is now all on you.

Marketing 136

Marketing Analytics Machine Learning Strategy 136

Jet Global

MAY 1, 2023

Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. Commercial vs. Internal Apps Any organization that develops or deploys a software application often has a need to embed analytics inside its application. CRM, ERP, EHR/EMR) or portals (e.g., intranets or extranets).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52