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How to Work Through a Regression Machine Learning Project in Weka Step-By-Step - Machine Learning Mastery

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The fastest way to get good at applied machine learning is to practice on end-to-end projects. In this post you will discover how to work through a regression problem in Weka, end-to-end. Step-By-Step Regression Machine Learning Project Tutorial in Weka Photo by vagawi, some rights reserved. This tutorial will walk you through the key steps required to complete a machine learning project in Weka. Weka is the best platform for beginners getting started in applied machine learning.


Applied Machine Learning With Weka Mini-Course - Machine Learning Mastery

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Machine learning is a fascinating study, but how do you actually use it on your own problems? You may be confused as to how best prepare your data for machine learning, which algorithms to use or how to choose one model over another. In this post you will discover a 14-part crash course into applied machine learning using the Weka platform without a single mathematical equation or line of programming code. Applied Machine Learning With Weka Mini-Course Photo by Leon Yaakov, some rights reserved. Before we get started, let's make sure you are in the right place.


Standard Machine Learning Datasets for Imbalanced Classification

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An imbalanced classification problem is a problem that involves predicting a class label where the distribution of class labels in the training dataset is skewed. Many real-world classification problems have an imbalanced class distribution, therefore it is important for machine learning practitioners to get familiar with working with these types of problems. In this tutorial, you will discover a suite of standard machine learning datasets for imbalanced classification. Standard Machine Learning Datasets for Imbalanced Classification Photo by Graeme Churchard, some rights reserved. Binary classification predictive modeling problems are those with two classes.


A Tour of the Weka Machine Learning Workbench - Machine Learning Mastery

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Weka is an easy to use and powerful machine learning platform. It provides a large number of machine learning algorithms, feature selection methods and data preparation filters. In this post you will discover the Weka machine learning workbench and take a tour of the key interfaces that you can use on your machine learning projects. The entry point into the Weka interface is the Weka GUI Chooser. It is an interface that lets you choose and launch a specific Weka environment.


Project in Python - Breast Cancer Classification with Deep Learning - DataFlair

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If you want to master Python programming language then you can't skip projects in Python. After publishing 4 advanced python projects, DataFlair today came with another one that is the Breast Cancer Classification project in Python. To crack your next Python Interview, practice these projects thoroughly and if you face any confusion, do comment, DataFlair is always ready to help you. An intensive approach to Machine Learning, Deep Learning is inspired by the workings of the human brain and its biological neural networks. Architectures as deep neural networks, recurrent neural networks, convolutional neural networks, and deep belief networks are made of multiple layers for the data to pass through before finally producing the output.