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Machine Learning for Computer Scientists and Data Analysts: From an Applied Pers
US $138.00
ApproximatelyRM 586.32
Condition:
Brand New
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Located in: Fairfield, Ohio, United States
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eBay item number:388645757773
Item specifics
- Condition
- Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
- ISBN-13
- 9783030967581
- Type
- NA
- Publication Name
- NA
- ISBN
- 9783030967581
About this product
Product Identifiers
Publisher
Springer International Publishing A&G
ISBN-10
3030967581
ISBN-13
9783030967581
eBay Product ID (ePID)
20061243508
Product Key Features
Book Title
Machine Learning for Computer Scientists and Data Analysts : from an Applied Perspective
Number of Pages
Xv, 458 Pages
Language
English
Topic
General, Electronics / Circuits / General, Electronics / General, Cybernetics
Publication Year
2023
Illustrator
Yes
Genre
Computers, Technology & Engineering, Science
Format
Trade Paperback
Dimensions
Item Weight
25.5 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Dewey Edition
23
Number of Volumes
1 vol.
Dewey Decimal
006.31
Table Of Content
Introduction.- Metadata Extraction and Data Preprocessing.- Data Exploration.- Practice Exercises.- Supervised Learning.- Unsupervised Learning.- Reinforcement Learning.- Model Evaluation and Optimization.- ML in Computer vision - autonomous driving and object recognition.- ML in Health-care - ECG and EEG analysis.- ML in Embedded Systems - resource management.- ML for Security (Malware).- ML in Big-data Analytics.- ML in Recommender Systems.- ML for Ontology Acquisition from Text and Image Data.- Adversarial Learning.- Graph Adversarial Neural Networks.- Graph Convolutional Networks.- Hardware for Machine Learning.- Software Frameworks.
Synopsis
This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks. Most importantly, this book helps readers to understand the concepts of ML algorithms and enables them to develop the skills necessary to choose an apt ML algorithm for a problem they wish to solve. In addition, this book includes numerous case studies, ranging from simple time-series forecasting to object recognition and recommender systems using massive databases. Lastly, this book also provides practical implementation examples and assignments for the readers to practice and improve their programming capabilities for the ML applications.
LC Classification Number
TK7867-7867.5
Item description from the seller
Seller feedback (1,053,932)
- r***a (2065)- Feedback left by buyer.Past monthVerified purchaseFast shipping. Great packaging.
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Seller feedback (1,053,932)
- r***a (2065)- Feedback left by buyer.Past monthVerified purchaseFast shipping. Great packaging.
- o***e (1485)- Feedback left by buyer.Past monthVerified purchaseQuickly shipped! Thank you!
- k***d (2972)- Feedback left by buyer.Past monthVerified purchaseExemplary