Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Paperback. Etat : new. Paperback. The rapid growth of digital platforms has led to a huge increase in user-generated text, especially movie reviews. Manually analyzing such data is difficult and time-consuming. Sentiment Analysis, an important area of Natural Language Processing (NLP), helps identify opinions expressed in text automatically. This study develops a deep learning-based system to classify movie reviews as positive or negative.The IMDB dataset of 50,000 labeled reviews was used. Data preprocessing included removing HTML tags, normalization, tokenization, stop-word removal, and stemming. The processed text was converted into numerical form using word embeddings to capture meaning.A Bidirectional LSTM model was used, which reads text in both directions to understand context better than traditional models. The model was trained with Adam optimizer and Binary Cross-Entropy loss, with early stopping to reduce overfitting.Results showed about 88.5% accuracy, proving the model's effectiveness. This approach can be applied in recommendation systems, social media analysis, and feedback evaluation. Future work may include using advanced models like BERT and handling sarcasm and multilingual data. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9786209881541
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Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9786209881541
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Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9786209881541
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9786209881541
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 124 pp. Englisch. N° de réf. du vendeur 9786209881541
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 124 pp. Englisch. N° de réf. du vendeur 9786209881541
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Vendeur : CitiRetail, Stevenage, Royaume-Uni
Paperback. Etat : new. Paperback. The rapid growth of digital platforms has led to a huge increase in user-generated text, especially movie reviews. Manually analyzing such data is difficult and time-consuming. Sentiment Analysis, an important area of Natural Language Processing (NLP), helps identify opinions expressed in text automatically. This study develops a deep learning-based system to classify movie reviews as positive or negative.The IMDB dataset of 50,000 labeled reviews was used. Data preprocessing included removing HTML tags, normalization, tokenization, stop-word removal, and stemming. The processed text was converted into numerical form using word embeddings to capture meaning.A Bidirectional LSTM model was used, which reads text in both directions to understand context better than traditional models. The model was trained with Adam optimizer and Binary Cross-Entropy loss, with early stopping to reduce overfitting.Results showed about 88.5% accuracy, proving the model's effectiveness. This approach can be applied in recommendation systems, social media analysis, and feedback evaluation. Future work may include using advanced models like BERT and handling sarcasm and multilingual data. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9786209881541
Quantité disponible : 1 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering. N° de réf. du vendeur 9786209881541
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