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scikit-learn-04-training-a-machine-learning-model.json
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scikit-learn-04-training-a-machine-learning-model.json
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{
"copyright_text": "Standard YouTube License",
"description": "Now that we're familiar with the famous iris dataset, let's actually use a classification model in scikit-learn to predict the species of an iris! We'll learn how the K-nearest neighbors (KNN) model works, and then walk through the four steps for model training and prediction in scikit-learn. Finally, we'll see how easy it is to try out a different classification model, namely logistic regression.\n\nThis is the fourth video in the series, `Introduction to machine learning with scikit-learn <http://www.dataschool.io/machine-learning-with-scikit-learn/>`__. The notebook and resources shown in the video are available on `GitHub <https://github.com/justmarkham/scikit-learn-videos>`__.",
"duration": 1188,
"language": "eng",
"recorded": "2015-04-29",
"related_urls": [
"http://www.dataschool.io/machine-learning-with-scikit-learn/",
"https://github.com/justmarkham/scikit-learn-videos"
],
"slug": "scikit-learn-04-training-a-machine-learning-model",
"speakers": [
"Kevin Markham"
],
"tags": [
"machine learning",
"data science",
"scikit-learn",
"tutorial",
"Data School",
"classification",
"KNN"
],
"thumbnail_url": "https://i1.ytimg.com/vi/RlQuVL6-qe8/maxresdefault.jpg",
"title": "Training a machine learning model with scikit-learn",
"videos": [
{
"type": "youtube",
"url": "https://www.youtube.com/watch?v=RlQuVL6-qe8"
}
]
}