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Why Businesses Should Use Machine Learning in 2023

Analytics Vidhya

Introduction In the words of Nick Bostrom, “Machine learning is the last invention that humanity will ever need to make.” Let’s start etymologically; machine learning (ML) is a subset of artificial intelligence (AI) that trains systems to apply specific solutions rather than providing the solution itself.

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How To Evaluate The Business Value Of a Machine Learning Model

Analytics Vidhya

The post How To Evaluate The Business Value Of a Machine Learning Model appeared first on Analytics Vidhya. In any data science project, the iterative process of refining the data, fine-tuning the models, deploying them is a continuous process. With all the advancements in tools, […].

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6 Ways Businesses Can Benefit From Machine Learning

KDnuggets

Machine learning is gaining popularity rapidly in the business world. Discover the ways that your business can benefit from machine learning.

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Machine learning does not produce value for my business. Why?

KDnuggets

What is going on when machine learning can't make the jump from testing to production, and so doesn't add any business value?

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Embedded Analytics: A Force Multiplier for Business

The possibilities for embedded analytics to drive real value for businesses, end users, and society are as fascinating as they are limitless. No matter the industry, brand after brand is finding that analytics can be the solution to a multitude of business challenges.

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How Data Science, Machine Learning and AI can help your business thrive

Data Insight

The world is buzzing about the possibilities that can be unlocked with AI, Machine Learning, and Data Science. But how exactly can you harness their potential to benefit your business?

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Big Data Hub

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements. Types of anomalies vary by enterprise and business function.

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The Big Payoff of Application Analytics

Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.

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Driving Business Impact for PMs

Speaker: Jon Harmer, Product Manager for Google Cloud

Move from feature factory to customer outcomes and drive impact in your business! Understand how your work contributes to your company's strategy and learn to apply frameworks to ensure your features solve user problems that drive business impact.

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7 Questions Every App Team Should Ask

In its 2020 Embedded BI Market Study, Dresner Advisory Services continues to identify the importance of embedded analytics in technologies and initiatives strategic to business intelligence. Discover the top seven requirements to consider when evaluating your embedded dashboards and reports.

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Reimagining CX: How to Implement Effective AI-Driven Transformations

Speaker: Steve Pappas, Chief Strategist, Startup and Early Stage Growth Advisor, Keynote Speaker, CX Podcaster

As businesses strive for success in an increasingly digitized world, delivering an exceptional customer experience has become paramount. This webinar with CX master Steve Pappas will unravel how conversational AI is transforming business-customer interactions and contact center operations globally.

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The Essential Guide to Analytic Applications

We interviewed 16 experts across business intelligence, UI/UX, security and more to find out what it takes to build an application with analytics at its core. No matter where you are in your analytics journey, you will learn about emerging trends and gather best practices from product experts.

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Modern Data Architecture for Embedded Analytics

Discover the pros and cons of each approach, plus how to choose the right architecture for your business priorities, timeline, and customers. You’ll learn: 7 approaches to data architecture for embedded analytics—from a transactional database to a columnar or in memory database.

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The Business Value of MLOps

As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models. It is based on interviews with MLOps user companies and several MLOps experts. Which organizational challenges affect MLOps implementations.

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AI in Manufacturing

In our AI in Manufacturing eBook, you can learn how to solve your most urgent manufacturing and business needs with an enterprise AI platform. Get this eBook to learn about: Achieving ROI with AI and delivering valuable results with urgency. Their problems and needs don’t change, but the technology and solutions do.