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The project is a simple sentiment analysis using NLP. The project in written in python with Jupyter notebook. It shows how to do text preprocessing (removing of bad words, stop words, lemmatization, tokenization). It further shows how to save a trained model, and use the model in a real life suitation. The machine learning model used here is k-Nearest Neighbor which is used to build the model. Various performance evaluation techniques are used, and they include confusion matrix, and Scikit-learn libraries classification report which give the accuracy, precision, recall and f1- score preformance of the model. The target values been classified are positive and negative review.

Jupyter Notebook 100.00%
data-science jupyter-notebook knn-classification machine-learning nlp numpy pandas python scikitlearn-machine-learning sentiment-analysis sklearn tokenization webscraping

sentiment-analysis-nlp-with-python's Introduction

Hello! I'm Ri

Enjoys learning new things and meeting new people to broaden my knowledge and perspective. Enthusiastic in generating insights for data-driven decision making. Iโ€™ve found that programming broaden my horizon and push my limit even more, which is why I decided to keep learning and achieve more.

๐Ÿ” You Can Find Me at

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โญ My Repositories

๐ŸŽ“ Courses DQLab Data Analyst Career Track ยท Progate
โš™ Projects Simple NLP . Android Studio

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