Towards AI

NOVEMBER 6, 2024

Last Updated on November 6, 2024 by Editorial Team Author(s): Talha Nazar Originally published on Towards AI. This story explores CatBoost, a powerful machine-learning algorithm that handles both categorical and numerical data easily. CatBoost is a powerful, gradient-boosting algorithm designed to handle categorical data effectively.

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Ocean Protocol

NOVEMBER 28, 2024

Introduction The Formula 1 Prediction Challenge: 2024 Mexican Grand Prix brought together data scientists to tackle one of the most dynamic aspects of racing — pit stop strategies. Firepig refined predictions using detailed feature engineering and cross-validation.

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Data Science Dojo

AUGUST 19, 2024

They dive deep into artificial neural networks, algorithms, and data structures, creating groundbreaking solutions for complex issues. Describe the backpropagation algorithm and its role in neural networks. Backpropagation is an algorithm used to train neural networks. What are some ethical considerations in AI development?

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DrivenData Labs

MAY 22, 2024

Results of the Hindcast Stage ¶ The Water Supply Forecast Rodeo is being held over multiple stages from October 2023 through July 2024. Gradient-boosted trees were popular modeling algorithms among the teams that submitted model reports, including the first- and third-place winners. Image courtesy of USBR.

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ODSC - Open Data Science

OCTOBER 24, 2023

Then, how to essentially eliminate training, thus speeding up algorithms by several orders of magnitude? My NoGAN algorithm, probably for the first time, comes with the full multivariate KS distance to evaluate results. He is the author of multiple books, including “Synthetic Data and Generative AI” (Elsevier, 2024).

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Pickl AI

SEPTEMBER 17, 2024

Machine Learning (ML) is a subset of AI that focuses on developing algorithms and statistical models that enable systems to perform specific tasks effectively without being explicitly programmed. Clustering algorithms, such as K-Means and DBSCAN, are common examples of unsupervised learning techniques.

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DagsHub

APRIL 21, 2024

Autonomous Vehicles: Automotive companies are using ML models for autonomous driving systems including object detection, path planning, and decision-making algorithms. MLOps ensures the reliability and safety of these models through rigorous testing, validation, and continuous monitoring in real-world driving conditions.

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