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Spatial Intelligence: Why GIS Practitioners Should Embrace Machine Learning- How to Get Started.

Towards AI

Created by the author with DALL E-3 Statistics, regression model, algorithm validation, Random Forest, K Nearest Neighbors and Naïve Bayes— what in God’s name do all these complicated concepts have to do with you as a simple GIS analyst? You just want to create and analyze simple maps not to learn algebra all over again.

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Data Science Journey Walkthrough – From Beginner to Expert

Smart Data Collective

Data scientists use algorithms for creating data models. Whereas in machine learning, the algorithm understands the data and creates the logic. Learning the various categories of machine learning, associated algorithms, and their performance parameters is the first step of machine learning.

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When Should AI Step Aside? Understanding Cultural Values in AI Systems

NYU Center for Data Science

CDS Faculty Fellow Umang Bhatt l eading a practical workshop on Responsible AI at Deep Learning Indaba 2023 in Accra In Uganda’s banking sector, AI models used for credit scoring systematically disadvantage citizens by relying on traditional Western financial metrics that don’t reflect local economic realities.

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An Analysis of the Loss Functions in Keras CV Tutorials

Heartbeat

I was interested to see what types of problems were solved and which particular algorithms were used with the different loss functions. Although I’m well versed in certain machine learning algorithms for building models with structured data, I’m much newer to computer vision, so exploring the computer vision tutorials is interesting to me.

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Introducing ?YOLO-NAS: A New State-of-the-Art for Object Detection

Heartbeat

But just because we have all these YOLOs doesn’t mean that deep learning for object detection is a dormant area of research. Listen to our own CEO Gideon Mendels chat with the Stanford MLSys Seminar Series team about the future of MLOps and give the Comet platform a try for free ! Innovation and academia go hand-in-hand.

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The Ultimate Guide to LLMs and NLP for Content Marketing

Heartbeat

It entails creating and using algorithms and methods to provide computers with the ability to recognize, decipher, and produce human language in a natural and meaningful manner. It entails employing algorithms and techniques to process and extract meaning from human language. Innovation and academia go hand-in-hand. articles, videos).

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What are some ethical considerations when using Generative AI

Dataconomy

This technology, which leverages machine learning algorithms to generate text, images, music, and even code, is becoming an integral part of our digital landscape. Additionally, incorporating fairness constraints into the AI’s learning process can help mitigate bias.

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