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You're reading from  Hands-On Recommendation Systems with Python

Product typeBook
Published inJul 2018
Reading LevelExpert
PublisherPackt
ISBN-139781788993753
Edition1st Edition
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Rounak Banik
Rounak Banik
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Rounak Banik

Rounak Banik is a Young India Fellow and an ECE graduate from IIT Roorkee. He has worked as a software engineer at Parceed, a New York start-up, and Springboard, an EdTech start-up based in San Francisco and Bangalore. He has also served as a backend development instructor at Acadview, teaching Python and Django to around 35 college students from Delhi and Dehradun. He is an alumni of Springboard's data science career track. He has given talks at the SciPy India Conference and published popular tutorials on Kaggle and DataCamp.
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Evaluation metrics

In this section, we will take a look at a few metrics that will allow us to mathematically quantify the performance of our classifiers, regressors, and filters.

Accuracy

Accuracy is the most widely used metric to gauge the performance of a classification model. It is the ratio of the number of correct predictions to the total number of predictions made by the model:

Root mean square error

The Root Mean Square Error (or RMSE) is a metric widely used to gauge the performance of regressors...

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Hands-On Recommendation Systems with Python
Published in: Jul 2018Publisher: PacktISBN-13: 9781788993753

Author (1)

author image
Rounak Banik

Rounak Banik is a Young India Fellow and an ECE graduate from IIT Roorkee. He has worked as a software engineer at Parceed, a New York start-up, and Springboard, an EdTech start-up based in San Francisco and Bangalore. He has also served as a backend development instructor at Acadview, teaching Python and Django to around 35 college students from Delhi and Dehradun. He is an alumni of Springboard's data science career track. He has given talks at the SciPy India Conference and published popular tutorials on Kaggle and DataCamp.
Read more about Rounak Banik