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<h3>Naive Bayes Tutorial for Machine Learning</h3><p>I am new in Payton programming language and Machine Learning, I am practicing Machine Learning algorithms so in an exercise where I use the algorithm of Chapter 12 Naive Bayes of the Book machine learning algorithms from scratch works well with the dataset of Iris.csv but when doing the exercise with another dataset of  </p>

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<h3>Quantum Computers Can Now Do Machine Learning  We Just Need </h3><p>The goal is to use quantum computers to create new classifiers that generate more sophisticated data maps. In doing that, researchers will be able to develop more effective AI that can, for  </p>

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<h3>Train Classification Models in Classification Learner App </h3><p>On the Apps tab, in the Machine Learning group, click Classification Learner. Click New Session and select data from the workspace or from file. Specify a response variable and variables to use as predictors. See Select Data and Validation for Classification Problem. </p>

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On the Apps tab, in the Machine Learning group, click Classification Learner. Click New Session and select data from the workspace or from file. Specify a response variable and variables to use as predictors. See Select Data and Validation for Classification Problem.

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<h3>How to Save Your Machine Learning Model and Make Predictions </h3><p>1. Finalize a Machine Learning Model. Perhaps the most neglected task in a machine learning project is how to finalize your model. Once you have gone through all of the effort to prepare your data, compare algorithms and tune them on your problem, you actually need to create the final model that you intend to use to make new predictions. </p>

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<h3>The 10 Algorithms Machine Learning Engineers Need to Know</h3><p>Machine learning algorithms can be divided into 3 broad categories  supervised learning, unsupervised learning, and reinforcement learning.Supervised learning is useful in cases where a property (label) is available for a certain dataset (training set), but is missing and needs to be predicted for other instances. </p>

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<h3>Machine Learning Classifier evaluation using ROC and CAP </h3><p>Machine Learning Classifier evaluation using ROC and CAP Curves In this article, Ill explore what ROC and CAP are and how we can use Python and a dummy dataset to create these curves. Even after exploring many articles on CAP Curve, I couldnt find an article that explained in detail how to create them, which is why I am writing this article. </p>

Machine Learning Classifier evaluation using ROC and CAP

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<h3>A new machine learning model can classify lung cancer slides </h3><p>The study demonstrates that machine learning can achieve high performance on a challenging image classification task and has the potential to greatly assist pathologists in lung cancer classification. </p>

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<h3>How to Save Your Machine Learning Model and Make Predictions </h3><p>1. Finalize a Machine Learning Model. Perhaps the most neglected task in a machine learning project is how to finalize your model. Once you have gone through all of the effort to prepare your data, compare algorithms and tune them on your problem, you actually need to create the final model that you intend to use to make new predictions. </p>

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<h3>New models sense human trust in smart machines  ScienceDaily</h3><p>New 'classification models'sense how well humans trust intelligent machines they collaborate with, a step toward improving the quality of interactions and teamwork. The longterm goal of the  </p>

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<h3>Types of classification algorithms in Machine Learning</h3><p>In machine learning and statistics, classification is a supervised learning approach in which the computer program learns from the data input given to it and then uses this learning to classify new </p>

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