Artificial Intelligence Concepts : Complete Course
What you'll learn
- Foundational Understanding of Mathematical Concepts in Machine Learning
- Application of Mathematics to Neural Networks
- Math-Driven Problem Solving in Deep Learning
- Advanced Optimization and Regularization Techniques
Requirements
- Basic understanding of algebra, including equations, functions, and basic operations.
- Familiarity with basic concepts of calculus, including limits, derivatives, and integrals.
- Basic knowledge of probability and statistics, including concepts of probability distributions, mean, and variance.
- Basic programming skills in a language like Python, including variables, loops, and functions.
- Basic knowledge of machine learning concepts, such as supervised and unsupervised learning.
Description
Delve into the captivating world where mathematics intertwines with the cutting-edge realm of Artificial Intelligence. Welcome to "Heart of AI: Mathematical Marvels in Machine Learning," a meticulously crafted Udemy course that illuminates the profound role of mathematical principles in shaping the landscape of modern machine learning.
Unlock the enigma behind AI algorithms as you embark on a journey that demystifies the complex equations and theorems driving machine learning innovations. Designed for both aspiring and seasoned data enthusiasts, this course transcends mere implementation and guides you through the mathematical core, empowering you to grasp the inner workings of AI models with clarity.
What You'll Learn:
Foundations of Optimization: Discover the beauty of optimization techniques such as gradient descent, Newton's method, and conjugate gradient descent. Gain a deep understanding of how these mathematical marvels underpin the process of fine-tuning AI models for unparalleled performance.
Linear Algebra Mastery: Immerse yourself in the elegant world of linear algebra, where matrices, vectors, and eigenvalues play a pivotal role in expressing and transforming data. Witness the power of linear algebra in crafting neural networks and dimensionality reduction methods.
Probability and Statistics Unveiled: Unravel the secrets of probability distributions, statistical inference, and hypothesis testing—the bedrock of AI's decision-making prowess. Witness the application of these principles in designing Bayesian networks and Gaussian processes.
Functional Analysis in Feature Spaces: Explore the intriguing concept of functional analysis and its implications in feature engineering and kernel methods. Delve into support vector machines, kernel PCA, and other advanced techniques that capitalize on this mathematical foundation.
Real-world Examples and Practical Insights: This course bridges theory and practice seamlessly by infusing every concept with real-world examples and practical insights. From training a neural network to identifying patterns in complex datasets, you'll witness firsthand how the mathematical concepts you learn are translated into tangible AI applications.
Embark on a transformative learning experience guided by engaging lectures, interactive exercises, and captivating case studies. Whether you're an AI enthusiast seeking to unravel the mathematical fabric of machine learning or a professional aiming to fortify your expertise, "Heart of AI: Mathematical Marvels in Machine Learning" is your compass to navigate the intricate terrain of AI's mathematical heart. Enroll now and embark on a journey that deepens your understanding, ignites your curiosity, and empowers you to shape the future of AI.
Who this course is for:
- People interested in Machine Learning (With basic programming background)
Instructor
- 4.4 Instructor Rating
- 31 Reviews
- 286 Students
- 2 Courses
Hi, my name is Emiliano Lako, and I am currently a student pursuing a degree in Electronics Engineering. I have always been passionate about technology and innovation, which is what drew me to the field of engineering in the first place.
Throughout my academic journey, I have excelled in subjects such as calculus, physics, and computer programming, demonstrating a natural aptitude for math and science. I have also sought out practical experience through internships and research projects, expanding my knowledge and skills in the field.
Outside of my studies, I am an active member of various student organizations related to engineering and technology. I take on leadership roles in these groups, organizing events and initiatives that promote collaboration and innovation among students.
After completing my degree, my goal is to pursue a career in the electronics industry. I am passionate about developing cutting-edge technologies that can make a positive impact on society, and I am confident that my technical proficiency, strong work ethic, and dedication to innovation will allow me to make a valuable contribution to the field of engineering.