Track My Order
Help Centre
Likes
My Wish ListsLogin / Join
Booktopia
Australia's local bookstore
Get Free Shipping on orders over $79
Machine Learning and Data Science : Fundamentals and Applications - Prateek Agrawal

Machine Learning and Data Science

Fundamentals and Applications

By: Prateek Agrawal, Charu Gupta, Anand Sharma, Vishu Madaan, Nisheeth Joshi

eText | 25 July 2022 | Edition Number 1

At a Glance

eText

$285.99

or 4 interest-free payments of $71.50 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

MACHINE LEARNING AND DATA SCIENCE

Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia.

Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms.

These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.

on
Desktop
Tablet
Mobile

You Can Find This eBook In

Non-FictionComputing & I.T.Computer Science

More in Computer Science

Amazon.com : Get Big Fast - Robert Spector

eBOOK

Amazon.com

Get Big Fast

eBook

$22.99

Learning Under Algorithmic Conditions - Elizabeth de Freitas

eBOOK

Learning Under Algorithmic Conditions

eBook

RRP $49.16

$39.99

19%
OFF

This product is categorised by