धन उगाहना 15 सितंबर, 2024 – 1 अक्टूबर, 2024 धन उगाहने के अभियान के बारे में

Pattern Recognition and Machine Learning. Solutions to...

Main
Computers - Artificial Intelligence (AI)
Pattern Recognition and Machine...

Pattern Recognition and Machine Learning. Solutions to Exercises: Web-Edition

Markus Svensén, Christopher M. Bishop

0 / 0

यह पुस्तक आपको कितनी अच्छी लगी?

फ़ाइल की गुणवत्ता क्या है?

पुस्तक की गुणवत्ता का मूल्यांकन करने के लिए यह पुस्तक डाउनलोड करें

डाउनलोड की गई फ़ाइलों की गुणवत्ता क्या है?

This is the solutions manual (web-edition) for the book Pattern Recognition and Machine Learning (PRML; published by Springer in 2006). It contains solutions to the www exercises. This release was created September 8, 2009.

श्रेणियाँ:

Computers - Artificial Intelligence (AI)

साल:

2009

संस्करण:

1; Sep, 2009

प्रकाशन:

Self-published

भाषा:

english

पृष्ठ:

101

श्रृंखला:

Information Science and Statistics

फ़ाइल:

PDF, 1.32 MB

IPFS:

,

english, 2009

कॉपीराइट धारक की शिकायत के कारण यह पुस्तक डाउनलोड के लिए उपलब्ध नहीं है

Beware of he who would deny you access to information, for in his heart he dreams himself your master

— Pravin Lal

आप के लिए दिलचस्प हो सकता है

Shlomo Kashani — Deep Learning Interviews

Kevin P Murphy — Probabilistic Machine Learning: An Introduction Book 1

it-ebooks — 机器学习训练秘籍（Machine Learning Yearning 中文版）

马春鹏 — 模式识别与机器学习中文版（马春鹏）

Kevin P. Murphy [Murphy, Kevin P.] — Machine Learning: A Probabilistic Perspective

Jason Brownlee — Ensemble Machine Learning With Python: 7-Day Mini-Course

Ian Goodfellow, Yoshua Bengio and Aaron Courville — Deep Learning

Gilbert Strang — Linear Algebra and Learning from Data

Trevor Hastie, Robert Tibshirani, Jerome Friedman — The Elements of Statistical Learning: Data Mining, Inference, and Prediction.

Richard Dumont — Machine Learning: The Ultimate Beginners Guide: To Understanding Machine Learning Basics & Techniques

Andrew Ng — Machine Learning Yearning (Draft Version)

Jean Gallier, Jocelyn Quaintance — Linear Algebra for Computer Vision, Robotics, and Machine Learning

Richard O. Duda, Peter Elliot Hart, David G. Stork — Solutions manual to accompany pattern classification

Christopher M. Bishop，马春鹏 — 模式识别与机器学习

Andrew Ng — Machine Learning Yearning

Ryszard S. Michalski; Jaime G. Carbonell; Tom M. Mitchell — Machine Learning: An Artificial Intelligence Approach

Sergios Theodoridis — Machine Learning: A Bayesian and Optimization Perspective (Instructor's Solution Manual)

Simon O. Haykin, Yanbo Xue — Solutions Manual for Neural Networks and Learning Machines, 3rd Edition

Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani — Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence

Stuart J. Russell and Peter Norvig — Instructor’s Manual: Exercise Solutions for Artificial Intelligence A Modern Approach - Third Edition

Bengio, Yoshua; Courville, Aaron; Goodfellow, Ian J — Deep learning: adaptive computation and machine learning

Sutton, Richard S., Barto, Andrew G. — Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)

Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar — Foundations of Machine Learning, Second Edition [2nd Ed] (Instructor Res. n. 1 of 3, Solution Manual, Solutions)

Kevin P. Murphy — Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)

Kevin P. Murphy — Probabilistic Machine Learning: Advanced Topics

Lise Getoor, Ben Taskar — Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)

Michael Irwin Jordan — Learning in Graphical Models

Chandavarkar, B. R.;Weiss, Mark Allen — Data structures and algorithm analysis in C++

Shubham Tayal, Preetha Mary George, Parveen Singla, Utku Kose, Hemachandran K. — Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

Christopher M. Bishop — Pattern Recognition and Machine Learning

Dey, Nilanjan; Mahalle, Parikshit N.; Pathan, Mohd. Shafi; Wagh, Sanjeev — Applied machine learning for smart data analysis

David G. Stork — Solution Manual to accompany Pattern Classification (2nd ed.)

David Barber — Bayesian reasoning and machine learning

Patrick Hall, Navdeep Gill — An Introduction to Machine Learning Interpretability, Second Edition

Aurélien Géron — Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition (Third Early Release)

C. S. (Cheng Soon) Ong, M. P. (Marc Peter) Deisenroth, A. Aldo Faisal — Mathematics For Machine Learning (MML) Official Solutions (Instructor's Solution Manual)

Peter Wlodarczak — Machine Learning and Its Applications

Dirk P. Kroese, Zdravko Botev, Thomas Taimre, Radislav Vaisman — Data Science and Machine Learning: Mathematical and Statistical Methods (Chapman & Hall/Crc Machine Learning & Pattern Recognition)

Qiang Yang, Yu Zhang, Wenyuan Dai, Sinno Jialin Pan — Transfer Learning

Nitin Indurkhya, Fred J. Damerau (Editors) — Handbook of Natural Language Processing, Second Edition (Chapman & Hall CRC Machine Learning & Pattern Recognition Series)

Vladimir N. Vapnik — The Nature of Statistical Learning Theory (Second Edition)

Robi Polikar (auth.), Cha Zhang, Yunqian Ma (eds.) — Ensemble Machine Learning: Methods and Applications

सबसे उपयोगी शब्द

जुड़े हुए बुकलिस्ट