We can't find the internet
Attempting to reconnect
Something went wrong
Hang in there while we get back on track
£38.00
Cambridge University Press Cambridge Mathematics for Machine Learning Textbook
Price data checked 1 day ago
We'll watch every seller, every day. One email when your price arrives.
This is the usual price. Wait for it to drop, or tell us your number.
£38 today · usual range £33–£42 · best ever £33
NEW HERE?
Amazon shows you one price. We show you all of them.
Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.
WHAT'S ON THIS PAGE
when this has been cheap or pricey
where the price is heading next
all-time high & low, recent range
name your number, we'll email you
Price History & Forecast
Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.
Last 90 days · 90 data points
Price Distribution
Price distribution over 90 days • 5 price ranges
Price Analysis
Most common range: £37-38 (73 days, 81.1%)
Price range: £33 - £42
Price levels: 5 price ranges over 90 days
Description
Key Features
Comprehensive coverage of essential topics including linear algebra, analytic geometry, matrix decompositions, and vector calculus.
Provides a self-contained learning environment that bridges the gap between math theory and machine learning practice.
Designed with minimal prerequisites to make complex mathematical concepts accessible to students and professionals.
Includes vital training in optimization, probability, and statistics to support data science and computer science goals.
High-quality perfect binding format with 390 pages of detailed educational content from Cambridge University Press.
Product Specifications
- Format
- paperback
- ASIN
- 110845514X
- Domain
- Amazon UK
- Release Date
- 23 April 2020
- Listed Since
- 26 April 2019
Barcode
No barcode data available
Similar Products You Might Like
Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
Cambridge University Press
Advanced Mathematical Methods (London School of Economics Mathematics)
Cambridge University Press
Advanced Mathematical Methods (London School of Economics Mathematics)
Cambridge University Press
Statistical Learning for Biomedical Data (Practical Guides to Biostatistics and Epidemiology)
Cambridge University Press
Machine Learning Essentials: Practical Guide in R
CREATESPACE
All the Mathematics You Missed: But Need to Know for Graduate School
Cambridge University Press
Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels
Cambridge University Press
Density Ratio Estimation in Machine Learning
Cambridge University Press
A Gentle Introduction to Optimization
Cambridge University Press
Optimization: A Bootcamp for Machine Learning, Inverse Problems, and Control
Cambridge University Press
Introduction to the Mathematical and Statistical Foundations of Econometrics (Themes in Modern Econometrics)
Cambridge University Press
An Introduction to Optimization on Smooth Manifolds
Cambridge University Press
Bandit Algorithms
Cambridge University Press
Introduction to Algebraic Geometry
Cambridge University Press
Probability, Random Processes, and Statistical Analysis: Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance
Cambridge University Press
Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R
Apress
Springer Geometry of Deep Learning - Signal Processing Book
Springer
Machine Learning Made Visual with Python
Elsevier
Machine Learning in Medicine - a Complete Overview
Springer
Matrix Algebra: 1 (Econometric Exercises, Series Number 1)
Cambridge University Press
A First Course in Machine Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
CRC Press
Matroids: A Geometric Introduction
Cambridge University Press
Mathematical Problems in Data Science: Theoretical and Practical Methods
Springer
A Mathematical Primer for Social Statistics (Quantitative Applications in the Social Sciences)
Sage Publications