Machine Learning on Amazon Alexa Reviews Dataset | Machine Learning Project 13
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- Опубліковано 6 лют 2025
- This video tutorial explains how to implement machine learning on amazon Alexa reviews dataset that is available on Kaggle. The machine learning algorithm used in this video is SVM (support vector machine) / support vector machine classifier (SCV). If you want to know how to implement different machine learning classifiers such as Logistic Regression or Multinominal Naïve Bayes on this dataset, or if you want to know how to implement deep learning classifiers such as artificial neural networks or LSTM on this dataset, I’ve done separate videos on these topics as well.
The dataset used for the project is obtained from Kaggle and consists of nearly 3000 reviews from amazon users regarding various amazon Alexa products like Alexa echo, Alexa dot etc. Exploratory data analysis is performed on the dataset to analyse various columns and the data is visualized using count plots and pie charts. The reviews are then processed using various methods which involve lowercase conversion, URL removal, punctuation removal, tokenization, stop-word removal and stemming. The processed data is then separated into positive and negative reviews and are then visualized using Word clouds, as word clouds help to identify the most prominent/frequently used words. Machine Learning is then performed on the processed data using a Support Vector Machine Classifier (SVC).
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Word Cloud video:
• Word Cloud in python |...
Pandas tutorial Series:
• Pandas Tutorial Series
Visualisation Playlist:
• Visualizations
Link to the dataset on Kaggle:
www.kaggle.com...
NLP Playlist:
• Natural Language Proce...
GitHub Link for project code:
github.com/ros...
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