Description
Complete Mathematical Intro to Machine Learning is a course that covers the mathematical principles that power modern machine learning algorithms, published by Udemy Online Academy. This course provides a solid foundation in the mathematical principles that power modern machine learning algorithms. It is designed for individuals who want to understand not only how machine learning models work, but also why they work. By covering linear algebra, calculus, probability, and statistics, this course bridges the gap between theory and practice. Individuals will learn how these mathematical tools support algorithms such as regression, classification, and neural networks, enabling them to build a strong conceptual framework for advanced study and practical implementation in data science and artificial intelligence.
This comprehensive course is designed to take you from the fundamentals of machine learning to advanced techniques in regression, classification, clustering, and neural networks. Whether you are an individual, a data science enthusiast, or a professional looking to hone your skills, this course will give you the tools and intuition you need to work effectively with real-world data. Mathematical formulas are analyzed and thoroughly explained step-by-step. You will not only gain a theoretical understanding of machine learning, but also practical intuition and experience for future projects. By the end of the course, you will have a strong set of fundamental machine learning techniques, know when and how to apply them, and understand the mathematical theories that power them – all with practical, real-world relevance.
What you will learn in Complete Mathematical Intro to Machine Learning:
- Using Python and R for Machine Learning Models
- Learn the mathematical foundations of the most common machine learning frameworks
- Learn to differentiate machine learning models suitable for specific use cases
- Apply a refined toolbox of algorithms to data science problems
- Understand how to adapt different machine learning models for specific applications
- Experience coding examples to apply to other projects
- Experience practical mathematical examples of models
- Learn neural networks and decision trees
- Understand k-means clustering and KNN algorithms
- Learn support vector machine learning and logistic regression
- And…
Course specifications
Publisher: Udemy
Instructors: BlueGem Data Science
Language: English
Level: Introductory
Number of Lessons: 110
Duration: 11 hours and 15 minutes
Course topics
Complete Mathematical Intro to Machine Learning Prerequisites
Basic knowledge of High School mathematics
Pictures
Complete Mathematical Intro to Machine Learning introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 720p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
13.5 GB
