Tag: python

In this article series in which we are covering classification, we will get our hands dirty with Decision Trees using Scikit-Learn. We will use the Glass Identification data set from UCI to predict glass type.

Here is the link to the article:

Machine Learning – Decision Trees using Scikit-Learn

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In this article series in which we are covering classification, we will get our hands dirty with K Nearest Neighbors using Scikit-Learn. We will use the Glass Identification data set from UCI to predict glass type.

Here is the link to the article:

Machine Learning – K Nearest Neighbors using Scikit-Learn

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In this article series covering classification, we will get our hands dirty with Naive Bayes using Scikit-Learn. We will use the Glass Identification data set from UCI to predict glass type.

Here is the link to the article:

Machine Learning – Naive Bayes using Scikit-Learn

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In this article, we will introduce and demonstrate the concept of Cross Validation in Machine Learning.

Here is the link to the article:

Machine Learning – Understanding Cross Validation

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In Part-3 of this article series covering data preparation, we will introduce the steps for performing Categorical Data Encoding on the loaded data set that is already cleansed.

Here is the link to the article:

Machine Learning – Data Preparation – Part 3

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In Part-2 of this article series covering data preparation, we will introduce the steps for performing Data Imputation on the loaded data set.

Here is the link to the article:

Machine Learning – Data Preparation – Part 2

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In Part-1 of this article series covering data preparation, we will introduce the steps for performing Exploratory Data Analysis (EDA).

Here is the link to the article:

Machine Learning – Data Preparation – Part 1

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In Part-2 of this article series covering classification, we will get our hands dirty with Logistic Regression using Scikit-Learn. We will use the Heart Failure clinical records data set from UCI to predict death event.

Here is the link to the article:

Machine Learning – Logistic Regression using Scikit-Learn – Part 2

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In Part-6 of this article series, we will get our hands dirty with the Regularization techniques using Scikit-Learn. We will cover the three popular regularization techniques – LASSO, Ridge, and Elastic Net.

Here is the link to the article:

Machine Learning – Regularization using Scikit-Learn – Part 6

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