Embark on a comprehensive Python machine learning tutorial that guides you through building a sentiment analysis model using scikit-learn. Learn to classify text as positive or negative using Amazon reviews as training data. Explore essential concepts including data preprocessing, text vectorization with Bag of Words and TF-IDF, model selection, and evaluation techniques. Master practical skills such as using CountVectorizer, implementing various classification algorithms, improving model performance, and leveraging GridSearchCV for hyperparameter tuning. Gain hands-on experience with NLP techniques, model saving and loading, and creating a category classifier. By the end of this tutorial, you'll have a solid foundation in applying machine learning to real-world text classification problems using Python and scikit-learn.