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Create Gradio Demo for Speaker Verification

Analytics Vidhya

The post Create Gradio Demo for Speaker Verification appeared first on Analytics Vidhya. We will leverage the Gradio Python package for creating a web interface for the model and deploy our app on Hugging Face Spaces. Introduction on Speaker Verification Have you ever […].

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What Can You Do With GPT-4o? | Demo

Analytics Vidhya

Demo appeared first on Analytics Vidhya. Get ready, for this AI feat will completely change how we see the world! Did you find ChatGPT and GPT-3 to be impressive? You’re about to get your head blown away in many ways. With […] The post What Can You Do With GPT-4o?

Analytics 283
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8 Wild Demos of Google’s AI Agents

Analytics Vidhya

Google Workspace introduces an AI […] The post 8 Wild Demos of Google’s AI Agents appeared first on Analytics Vidhya. Google’s AI Agent integration into Google Search enhances research capabilities, while Gemini and Chrome enable secure browsing.

Analytics 254
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Google’s GenCast: Weather Forecasting with GenCast Mini Demo

Analytics Vidhya

Over centuries, we have been doing multiple things to predict the weather, such as listening to the cricket chirps or looking to the stars for […] The post Google’s GenCast: Weather Forecasting with GenCast Mini Demo appeared first on Analytics Vidhya.

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Webinar On-Demand: 3 Ways to Make Your Operational Execution More Robust With S&OE

Speaker: Sander van Lokven and N.S. Krishnan

How to use scenarios for on the fly decision making (demo). The impact on short term plans when the unexpected happens. 3 ways to increase rigor in your sales and operations execution to deal with the unexpected.

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ON DEMAND WEBINAR: Data Observability Demo Day

DataKitchen

The post ON DEMAND WEBINAR: Data Observability Demo Day first appeared on DataKitchen. That missing piece that connects data system expectations and reality is a ‘Data Journey.’ It is the missing piece of our data systems.

Testing 130
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How to Implement Data Engineering in Practice?

Analytics Vidhya

Components of Data Engineering Object Storage Object Storage MinIO Install Object Storage MinIO Data Lake with Buckets Demo Data Lake Management Conclusion References What is Data Engineering? Image Source: GitHub Table of Contents What is Data Engineering? Initially, we have the definition of Software […].

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Supply Chain Network Design: What Are Your Options?

Speaker: Paul van Nierop, Senior Supply Chain Consultant, AIMMS

A short demo of AIMMS Network Design. After the webinar, you will be equipped to decide which technology fits your organization best. This webinar shares: What is supply chain network design? The main network design technologies and their pros, cons, and capabilities.

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Supply Chain Network Design in 30 Minutes

Speaker: Catalina Perez Leiva

Learn how AIMMS Network Design helps you run various scenarios to make informed decisions, all with personal, high-care implementation support and onboarding. AIMMS Network Design features, functions, and technology: Use cases.

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Easily Build an Optimization App and Empower Your Data

Speaker: Gertjan de Lange

In this short demo, you will: See how to quickly model sets, parameters, variables, and a multitude of constraints that will define your mathematical formulation. Watch this exclusive demo today! Experience how efficient you can be when you fit your model with actionable data. Don't let uncertainty drive your business.

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Best Practices for Accelerating the Sales Process

Think about it: with outbound prospecting, requests from management, scheduled demos, and inbound calls, chaos can quickly work its way into your strategy, deeming a “speed wins” selling mentality downright ineffective. The bottom line is that, in B2B sales, speed is useless without control.

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Data Analytics in the Cloud for Developers and Founders

Speaker: Javier Ramírez, Senior AWS Developer Advocate, AWS

A live demo of lake formation. In this session, we address common pitfalls of building data lakes and show how AWS can help you manage data and analytics more efficiently. Javier Ramirez will present: The typical steps for building a data lake. Navigating idle clusters and bottlenecks.