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Decision Tree Classification- A Guide to Supervised Machine Learning Algorithm

Pickl AI

One of the most popular algorithms in Machine Learning are the Decision Trees that are useful in regression and classification tasks. Decision trees are easy to understand, and implement therefore, making them ideal for beginners who want to explore the field of Machine Learning. How Decision Tree Algorithm works?

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Feature scaling: A way to elevate data potential

Data Science Dojo

Feature Engineering is a process of using domain knowledge to extract and transform features from raw data. These features can be used to improve the performance of Machine Learning Algorithms. Normalization A feature scaling technique is often applied as part of data preparation for machine learning.

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How Decision Trees Handle Missing Values: A Comprehensive Guide

Pickl AI

In the world of Machine Learning and Data Analysis , decision trees have emerged as powerful tools for making complex decisions and predictions. These tree-like structures break down a problem into smaller, manageable parts, enabling us to make informed choices based on data. What is a Decision Tree?

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Predictive Analytics: 4 Primary Aspects of Predictive Analytics

Smart Data Collective

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

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Machine Learning with MATLAB and Amazon SageMaker

Flipboard

We have access to a large repository of labeled data generated from a Simulink simulation that has three possible fault types in various possible combinations (for example, one healthy and seven faulty states). The model can be tuned to match operational data from our real pump using parameter estimation techniques in MATLAB and Simulink.

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2024 Mexican Grand Prix: Formula 1 Prediction Challenge Results

Ocean Protocol

Using innovative approaches and advanced algorithms, participants modeled scenarios accounting for starting grid positions, driver performance, and unpredictable race conditions like weather changes or mid-race interruptions. His focus on track-specific insights and comprehensive data preparation set the model apart.

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Predictive Maintenance Using Isolation Forest

PyImageSearch

One such technique is the Isolation Forest algorithm, which excels in identifying anomalies within datasets. In this tutorial, you will learn how to implement a predictive maintenance system using the Isolation Forest algorithm — a well-known algorithm for anomaly detection. And Why Anomaly Detection?