Cantitate/Preț
Produs
Total produse
Vezi coșul
Introduction to Machine Learning with Applications in Information Security de Mark Stamp

Introduction to Machine Learning with Applications in Information Security: Chapman & Hall/CRC Machine Learning & Pattern Recognition

Autor Mark Stamp
en Limba Engleză Paperback – 19 dec 2024
Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 42971 lei  6-8 săpt.
  Taylor & Francis Ltd. – 19 dec 2024 42971 lei  6-8 săpt.
Hardback (2) 41054 lei  3-5 săpt. +4333 lei  6-10 zile
  Taylor & Francis – 12 iul 2017 41054 lei  3-5 săpt. +4333 lei  6-10 zile
  CRC Press – 27 sep 2022 52099 lei  6-8 săpt.

Din seria Chapman & Hall/CRC Machine Learning & Pattern Recognition

  • A First Course in Machine Learning
    Preț: 31305 lei
  • 9% Data Science and Machine Learning: Mathematical and Statistical Methods
    Preț: 61755 lei
  • 20% Transformers for Machine Learning: A Deep Dive
    Preț: 29844 lei
  • 20% The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions
    Preț: 49584 lei
  • Artificial Intelligence and Causal Inference
    Preț: 35369 lei
  • Deep and Shallow: Machine Learning in Music and Audio
    Preț: 35734 lei
  • 20% Handbook of Natural Language Processing
    Preț: 92143 lei
  • 8% Introduction to Machine Learning with Applications in Information Security
    Preț: 41054 lei
  • 31% Multi-Label Dimensionality Reduction
    Preț: 59154 lei
  • Sparse Modeling: Theory, Algorithms, and Applications
    Preț: 42259 lei
  • 27% Statistical Reinforcement Learning: Modern Machine Learning Approaches
    Preț: 26350 lei
  • 18% Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data
    Preț: 77984 lei
  • 27% Regularization, Optimization, Kernels, and Support Vector Machines
    Preț: 25981 lei
  • 43% Utility-Based Learning from Data
    Preț: 26641 lei
  • 26% Computational Trust Models and Machine Learning
    Preț: 27202 lei
  • 15% Deep Learning and Linguistic Representation
    Preț: 44804 lei
  • 30% Entropy Randomization in Machine Learning
    Preț: 26466 lei
  • 15% Machine Learning, Animated
    Preț: 65470 lei
  • 20% Ensemble Methods: Foundations and Algorithms
    Preț: 67278 lei
  • 20% A Concise Introduction to Machine Learning
    Preț: 38951 lei
  • 12% Bayesian Programming
    Preț: 29989 lei
  • 30% Machine Learning: An Algorithmic Perspective, Second Edition
    Preț: 43601 lei

Preț: 42971 lei

Nou

Puncte Express: 645
Preț estimativ în valută:
8227€ • 8440$ • 6927£

Carte tipărită la comandă

Livrare economică 26 februarie-12 martie

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781032207179
ISBN-10: 1032207175
Pagini: 534
Dimensiuni: 156 x 234 mm
Greutate: 0.69 kg
Editura: Taylor & Francis Ltd.
Seria Chapman & Hall/CRC Machine Learning & Pattern Recognition

Notă biografică

Mark Stamp is a Professor at San Jose State University, and the author of two textbooks, Information Security: Principles and Practice and Applied Cryptanalysis: Breaking Ciphers in the Real World. He previously worked at the National Security Agency (NSA) for seven years, which was followed by two years at a small Silicon Valley startup company.

Cuprins

  1. Preface
    About the Author
    1. What is Machine Learning?
    2. A Revealing Introduction to Hidden Markov Models
    3. Principles of Principal Component Analysis
    4. A Reassuring Introduction to Support Vector Machines
    5. A Comprehensible Collection of Clustering Concepts
    6. Many Mini Topics
    7. Deep Thoughts on Deep Learning
    8. Onward to Backpropagation
    9. A Deeper Diver into Deep Learning
    10. Alphabet Soup of Deep Learning Topics
    11. HMMs for Classic Cryptanalysis
    12. Image Spam Detection
    13. Image-Based Malware Analysis
    14. Malware Evolution Detection
    15. Experimental Design and Analysis
    16. Epilogue
    References
    Index