Your cart is currently empty!
Basic Math for AI: A Beginner’s Quickstart Guide to the Mathematical Foundations of Artificial Intelligence (AI Fundamentals)
Price: $14.99
(as of Jan 04,2025 20:57:56 UTC – Details)
Publisher : Book Bound Studios (June 7, 2024)
Language : English
Paperback : 190 pages
ISBN-10 : 1761590928
ISBN-13 : 978-1761590924
Item Weight : 10.7 ounces
Dimensions : 5.5 x 0.43 x 8.5 inches
Customers say
Customers find the book helpful for understanding math concepts like algebra, calculus, and probability. It explains things clearly and provides practical examples, making it easy to follow. Readers describe it as an excellent resource for anyone looking to understand math basics. They find the pacing well-crafted and enjoyable.
AI-generated from the text of customer reviews
Artificial intelligence (AI) is a rapidly growing field with countless applications in various industries. However, understanding the mathematical foundations of AI is essential for anyone looking to dive into this exciting field. In this beginner’s quickstart guide, we will cover the basic math concepts that form the backbone of AI.
1. Linear Algebra: Linear algebra is one of the most important mathematical concepts in AI. It deals with vectors, matrices, and their operations. In AI, we often use matrices to represent data and perform operations such as matrix multiplication, matrix inversion, and matrix factorization.
2. Calculus: Calculus is another crucial concept in AI, especially in optimization algorithms. Understanding calculus will help you grasp concepts like gradient descent, which is used to minimize loss functions in machine learning models.
3. Probability and Statistics: Probability and statistics play a significant role in AI, especially in probabilistic models and machine learning algorithms. Understanding concepts like probability distributions, expected value, variance, and hypothesis testing is essential for building robust AI models.
4. Optimization: Optimization is the process of finding the best solution among a set of feasible solutions. In AI, optimization algorithms are used to train machine learning models and fine-tune their parameters. Understanding optimization techniques like gradient descent, stochastic gradient descent, and Newton’s method is crucial for building efficient AI systems.
By mastering these basic math concepts, you will have a solid foundation to dive deeper into the world of artificial intelligence. Keep practicing and applying these concepts to real-world problems to enhance your understanding and skills in AI. Happy learning!
#Basic #Math #Beginners #Quickstart #Guide #Mathematical #Foundations #Artificial #Intelligence #Fundamentals,machine learning: an applied mathematics introduction
Leave a Reply