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How Light & Wonder built a predictive maintenance solution for gaming machines on AWS

AWS Machine Learning Blog

Working with AWS, Light & Wonder recently developed an industry-first secure solution, Light & Wonder Connect (LnW Connect), to stream telemetry and machine health data from roughly half a million electronic gaming machines distributed across its casino customer base globally when LnW Connect reaches its full potential.

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Machine Learning with MATLAB and Amazon SageMaker

Flipboard

In recent years, MathWorks has brought many product offerings into the cloud, especially on Amazon Web Services (AWS). First, we extract features from a subset of the full dataset using the Diagnostic Feature Designer app, and then run the model training locally with a MATLAB decision tree model.  Either Ubuntu or Linux.

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Time series forecasting with Amazon SageMaker AutoML

AWS Machine Learning Blog

SageMaker AutoMLV2 is part of the SageMaker Autopilot suite, which automates the end-to-end machine learning workflow from data preparation to model deployment. Data preparation The foundation of any machine learning project is data preparation.

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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Data Preparation for AI Projects Data preparation is critical in any AI project, laying the foundation for accurate and reliable model outcomes. This section explores the essential steps in preparing data for AI applications, emphasising data quality’s active role in achieving successful AI models.

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Understanding and Building Machine Learning Models

Pickl AI

Key steps involve problem definition, data preparation, and algorithm selection. Data quality significantly impacts model performance. For example, linear regression is typically used to predict continuous variables, while decision trees are great for classification and regression tasks.

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Large Language Models: A Complete Guide

Heartbeat

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

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Predicting the Future of Data Science

Pickl AI

Augmented Analytics Augmented analytics is revolutionising the way businesses analyse data by integrating Artificial Intelligence (AI) and Machine Learning (ML) into analytics processes. Dive Deep into Machine Learning and AI Technologies Study core Machine Learning concepts, including algorithms like linear regression and decision trees.