Hi 👋, I'm Nabiul Farhan Nabil

A Computer Science student who is passionate about Data Science

• 🔭 I’m currently working on Support Vectore Machine (SVM) on Twitter Dataset

• 🌱 I’m currently learning Python, SQL, MySQL

• 💬 Ask me about Machine Learning, AI, NLP

• 📫 How to reach me [email protected]

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Support Vector Machine

In this project I have taken the sentiment140 dataset. It contains 1,600,000 tweets extracted using the twitter api. The tweets have been labeled (0 = negative, 4 = positive). Here I have shown the process of tokenization, stemming, vectorization and how SVM works on the dataset. Three kernels of SVM is used here. They are Linear, Polynomial and Gaussian Kernel. The accuracy, precision, recall and f1-score is shown here for all three kernels. Different kernels are giving different results. Because the way of distrbuting data is differet for each of them.