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Advanced Machine Learning Deep (69 results)
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Hardcover. Condition: Good. No Jacket. 1st Edition. Book is in very good condition with the exception of a bump/indent to the top edge of the front and rear cover. Bottom cover corners bumped. This is why I listed it as good condition. Otherwise minor edgewear. Inside pages are clean and tight. No writing or marking.
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Paperback. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.82.
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Keras & Deep Learning: 100 Interview Questions (Advanced Topics in Machine Learning)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 15
Convert currency£ 11.98 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
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Machine Learning with Python: An Advanced Guide to Go Deep into Artificial Intelligence. Tools, Tips and Tricks for Going into Data Science and Data Analysis using Python and TensorFlow
Published by Independently published, 2019
ISBN 10: 1709584335 ISBN 13: 9781709584336
Language: English
£ 25.81
Convert currency£ 10 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: Brand New. 194 pages. 9.00x6.00x0.44 inches. In Stock.
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Condition: New.
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Condition: New.
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£ 46.18
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Add to basketPaperback. Condition: Brand New. 186 pages. 9.00x6.00x0.50 inches. In Stock.
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hardcover. Condition: New. Open Books is a nonprofit social venture that provides literacy experiences for thousands of readers each year through inspiring programs and creative capitalization of books.
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Machine Learning and Deep Learning Techniques for Medical Science (Artificial Intelligence (AI): Elementary to Advanced Practices)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 57.84
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Condition: New.
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£ 46
Convert currency£ 25 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketpaperback. Condition: New. New. book.
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Condition: New. Print on Demand.
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Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches (Artificial Intelligence (AI): Elementary to Advanced Practices)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 67.20
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£ 62
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Add to basketPaperback. Condition: New. New. book.
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Machine Learning: A Journey from Beginner to Advanced Including Deep Learning, Scikit-learn and Tensorflow White, Michael B.
Published by CreateSpace Independent Publishing Platform, 2018
ISBN 10: 1723484725 ISBN 13: 9781723484728
Language: English
Condition: New.
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Python advanced data analysis: machine learning. deep learning. and NLP instances(Chinese Edition)
ISBN 10: 7111617029 ISBN 13: 9787111617020
paperback. Condition: New. Language:Chinese.Paperback. Pub Date: 2019-01-01 Pages: 156 Publisher: Mechanical Industry Press This book introduces the broad base of advanced data analysis concepts. as well as * near database revolutions such as Neo4j. Elastic Search and MongoDB. This book discusses how to implement ETL technology including local crawling. and applies it to high-frequency algorithmic trading and goal-oriented dialogue.
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Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks
Published by Packt Publishing Limited, 2018
ISBN 10: 1788399900 ISBN 13: 9781788399906
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 41
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 821.
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Study of Advanced ML & DL Models for Credit Card Fraud Detection : A Comprehensive Survey on Advanced Techniques of Machine Learning and Deep Learning Approaches
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206180662 ISBN 13: 9786206180661
Language: English
£ 70.04
Convert currency£ 24.74 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Machine learning and deep learning (DL) techniques have shown promising results in detecting fraudulent activities. In this thesis, we propose approaches for credit card fraud detection that combine supervised and unsupervised learning techniques. We apply feature engineering techniques to extract relevant features from the credit card transaction dataset, followed by anomaly detection models that combine supervised ML, semi-supervised ML, and DL techniques. We analyze the dataset using various parameters and methods. Our study on various ML and DL methods in detecting fraudulent transactions are Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Support Vector Classifier (SVC) with Autoencoder, Linear Regression with Autoencoder, K-Nearest Neighbors (KNN), XGBoost, CatBoost, Adaboost, Gradient Boosting, Random Forest, Decision Tree, K-Means Clustering, LightBGM, Logistic Regression, logistic regression with undersampled data, Naive Bayes achieves, SVC achieves, Isolation Forest, and Local Outlier Factor. We evaluate our approach on a real-world credit card transaction dataset named Creditcard.csv from the Kaggle dataset.
