In this blog, we’ll continue to develop the Spam Detector classifier which we started in the previous blog. we have already prepared the Train and Test data in our last blog, lets now work on cleaning the data for the training . Data Transformation Let’s develop a subroutine to convert the HTML emails to text…
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Today lets create the SPAM Classifier. Spam classifier will detect whether an email is Spam or ham. We are going to use the Spam and Ham from Apache SpamAssassin’s dataset. Let’s download the dataset first. This blog is part of my #100daysofMLCode challenge and you can find all my previous blog here. import tarfile from…
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Binary Classifiers which we have created on Day 4 can distinguish between two classes, however, Multiclass Classifiers can differentiate between more than two class. Algorithms like Random Forest, Naive Bayes, and K-Nearest Neighbors are capable to handle the multiclass labels while other famous classification algorithms like SVM ( Support Vector Machine), Simple Gradient Descent cannot handle the…
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Classification is one the most common supervise learning task to predict the class type of the data. In day 4 of our #100DaysOfMLCode Challenge, we’ll try to prepare the small classifier. Problem statement: Predict the Soil Type of forest based on the input detail from the dataset. We are using the Forest Cover Type Dataset…
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We are going to evaluate our model in this blog. This is a continuation of the previous blog, #100DaysOfMLCode Challenge and we are going to created and evaluate the model In the first blog, we did data analysis and you can find the detail here. After that in the next blog, we prepared a pipeline…
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Today we are going to cleanse the data which we did analysis in the last post and create a small Linear Regression Model to perform Linear Regression on the cleansed data. Prepare Data for Machine Learning: Let’s first divide the entire data into two sets, training and other for testing. We are going to use SciKit-Learn to…
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In this blog series, I am planning to update my everyday learning related to #100DaysOfMLCode challenge. And if you are interested in the100 days of ML Code challenge, please follow this series and I’ll update my learning every day. #Day 1 – 100 Days Of ML Code : Simple data analysis Firstly, we are going to…
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