Python for Probability, Statistics, and Machine Learning - Image 1

£47.89

Springer Python for Probability, Statistics, and Machine Learning

Name: Python for Probability, Statistics, and Machine Learning
Brand: Springer
Price: 47.89 GBP
Availability: InStock

AI & Machine Learning

It has never been this cheap. We have no record of a lower price.

£48 today · cheaper than every other day in the last 3 months

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

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
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 26 days • 26 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 26 days • 1 price levels

Days at Price

Price Analysis

Most common price: £48 (26 days, 100.0%)

Price range: £48 - £48

Price levels: 1 different prices over 26 days

Description

Using a novel integration of mathematics and Python codes, this book illustrates the fundamental concepts that link probability, statistics, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also understand their relative strengths and weaknesses. To clearly connect theoretical concepts to practical implementations, the author provides many worked-out examples along with "Programming Tips" that encourage the reader to write quality Python code. The entire text, including all the figures and numerical results, is reproducible using the Python codes provided, thus enabling readers to follow along by experimenting with the same code on their own computers. Modern Python modules like Pandas, Sympy, Scikit-learn, Statsmodels, Scipy, Xarray, Tensorflow, and Keras are used to implement and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, interpretability, and regularization. Many abstract mathematical ideas, such as modes of convergence in probability, are explained and illustrated with concrete numerical examples. This book is suitable for anyone with undergraduate-level experience with probability, statistics, or machine learning and with rudimentary knowledge of Python programming.

Product Specifications

Brand: Springer
Format: paperback
ASIN: 3031046501
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 06 November 2023
Listed Since: 10 October 2023

Barcode

No barcode data available

Springer Python for Probability, Statistics, and Machine Learning

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Python for Probability, Statistics, and Machine Learning

Probability and Statistics for Data Science

Statistics Using Python

Probability and Statistics for Data Science

From Statistical Physics to Data-Driven Modelling: with Applications to Quantitative Biology

An Introduction to Statistics with Python: With Applications in the Life Sciences (Statistics and Computing)

Applied Statistics with Python: Two-Volume Set

Statistics and Data Visualisation with Python (Chapman & Hall/CRC The Python Series)

Think Stats: Exploratory Data Analysis

Introduction to Probabilistic and Statistical Methods with Examples in R: 176 (Intelligent Systems Reference Library, 176)

Practical Statistics for Data Scientists, 2e: 50+ Essential Concepts Using R and Python

Foundations of Data Science with Python (Chapman & Hall/CRC The Python Series)

Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

Essential Statistics for Data Science: A Concise Crash Course

Machine Learning – A Probabilistic Perspective

Theory of Stochastic Objects: Probability, Stochastic Processes and Inference (Chapman & Hall/CRC Texts in Statistical Science)

Statistical Inference and Machine Learning for Big Data (Springer Series in the Data Sciences)

CRC Standard Probability and Statistics Tables and Formulae, Student Edition

Probabilistic Data-Driven Modeling

Applied Probability: From Random Experiments to Random Sequences and Statistics

Mathematics and Programming for Machine Learning with R: From the Ground Up

Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics (Springer Texts in Statistics)

Introduction to Probability and Statistics for Data Science: with R

Probability and Statistics by Example