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DirectX Visualization Optimizes Analytics Algorithmic Traders

Smart Data Collective

Learn how DirectX visualization can improve your study and assessment of different trading instruments for maximum productivity and profitability. Let’s dive right into how DirectX visualization can boost analytics and facilitate testing for you as an Algo-trader, quant fund manager, etc. But first, What is DirectX Anyway?

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Demystifying Multimodal LLMs

Dataiku

Moreover, M-LLMs adeptly answer questions about visual content, aiding in tasks like image recognition and scene understanding. Additionally, we’ll explore their proficiency in tasks such as generating descriptive captions for images and answering questions about visual content.

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How to Create a Data Visualization Style Guide to Tell Great Stories (Part 2)

Depict Data Studio

Did you see Sara DeLong’s post on Why You Need to Create a Data Visualization Style Guide to Tell Great Stories? In my previous post I described how to identify if your team needs a Data Visualization Style Guide, how to secure buy-in from leadership and your coworkers, and some great resources to review before you get started.

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Data Visualization Libraries to Enhance Your Custom Analytics

Sisense

The world of data visualization is constantly evolving. If you’re reading this, it’s likely for one of two reasons: You need a visualization library for your project, or you’re curious about what’s changed since 2020 in terms of visualization libraries. Data visualizations are a vital part of embedded analytics.

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Generative AI: the Shortcut to Digital Modernisation

CIO Business Intelligence

Faster app development: By leveraging Generative AI, companies can automate documentation generation, improve software reusability, and seamlessly integrate AI functions such as chatbots and image recognition into low-code applications. The IT firm also partners with visionary partners to develop impactful solutions.

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Fearing the Wrong Thing

O'Reilly on Data

Some of that time is spent in pointless meetings, but much of “the rest of the job” is understanding the user’s needs, designing, testing, debugging, reviewing code, finding out what the user really needs (that they didn’t tell you the first time), refining the design, building an effective user interface, auditing for security, and so on.

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Application modernization overview

IBM Big Data Hub

Subsequent phases are build and test and deploy to production. Modernization teams perform their code analysis and go through several documents (mostly dated); this is where their reliance on code analysis tools becomes important. Let us explore the Generative AI possibilities across these lifecycle areas.