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Mathematical Foundation for AI and Machine Learning
Mathematical Foundation for AI and Machine Learning

Mathematical Foundation for AI and Machine Learning: Learn the core mathematical concepts for machine learning and learn to implement them in R and Python

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AU$14.99 AU$64.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Jul 2018 4hrs 15mins 1st Edition
Video
AU$14.99 AU$64.99
Subscription
Free Trial
Renews at AU$24.99p/m
Arrow left icon
Profile Icon Eduonix Learning Solutions
Arrow right icon
AU$14.99 AU$64.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Jul 2018 4hrs 15mins 1st Edition
Video
AU$14.99 AU$64.99
Subscription
Free Trial
Renews at AU$24.99p/m
Video
AU$14.99 AU$64.99
Subscription
Free Trial
Renews at AU$24.99p/m

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Key benefits

  • - Linear algebra notation is used in machine learning to describe the parameters and structure of different machine learning algorithms.
  • - Multivariate Calculus – This is used to supplement the learning part of machine learning.
  • - Probability Theory – The theories are used to make assumptions about the underlying data when we are designing these deep learning or AI algorithms.

Description

Artificial Intelligence has gained importance in the last decade with a lot depending on the development and integration of AI in our daily lives. The progress that AI has already made is astounding with innovations like self-driving cars, medical diagnosis and even beating humans at strategy games like Go and Chess. The future for AI is extremely promising and it isn’t far from when we have our own robotic companions. This has pushed a lot of developers to start writing codes and start developing for AI and ML programs. However, learning to write algorithms for AI and ML isn’t easy and requires extensive programming and mathematical knowledge. Mathematics plays an important role as it builds the foundation for programming for these two streams. And in this course, we’ve covered exactly that. We designed a complete course to help you master the mathematical foundation required for writing programs and algorithms for AI and ML.

Who is this book for?

Any one who wants to refresh or learn the mathematical tools required for AI and machine learning will find this course very useful

What you will learn

  • - Refresh the mathematical concepts for AI and Machine Learning
  • - Learn to implement algorithms in Python
  • - Understand the how the concepts extend for real-world ML problems

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 24, 2018
Length: 4hrs 15mins
Edition : 1st
Language : English
ISBN-13 : 9781789613209
Vendor :
Google
Category :
Languages :
Tools :

What do you get with a video?

Product feature icon Download this video in MP4 format
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
OR
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Product Details

Publication date : Jul 24, 2018
Length: 4hrs 15mins
Edition : 1st
Language : English
ISBN-13 : 9781789613209
Vendor :
Google
Category :
Languages :
Tools :

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Frequently bought together


Stars icon
Total AU$ 136.97 186.97 50.00 saved
Mathematical Foundation for AI and Machine Learning
AU$14.99 AU$64.99
Machine Learning Algorithms
AU$75.99
Artificial Intelligence and Machine Learning Fundamentals
AU$45.99
Total AU$ 136.97 186.97 50.00 saved Stars icon
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Table of Contents

5 Chapters
Introduction Chevron down icon Chevron up icon
Linear Algebra Chevron down icon Chevron up icon
Multivariate Calculus Chevron down icon Chevron up icon
Probability Theory Chevron down icon Chevron up icon
Probability Theory Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(1 Ratings)
5 star 100%
4 star 0%
3 star 0%
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1 star 0%
Daniel May 29, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good content for a beginner, helps remembering concepts studied in the past and to know new ones
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