Description
“ML from Zero: Machine Learning Math & Python from Scratch” is a course designed to help you understand machine learning from the ground up, published by the online learning platform Udemy. You will begin by developing essential Python programming skills and learning the mathematical foundations of machine learning—including statistics, probability, linear algebra, and optimization principles. The course guides you through the entire machine learning lifecycle: from data collection and preparation to algorithm selection, model training, and performance evaluation. You will explore fundamental techniques such as linear and logistic regression, classification, clustering, and other core learning methods, while discovering how computers identify patterns and make data-driven predictions. Through hands-on coding exercises and real-world examples, you will gain practical experience in implementing algorithms, analyzing datasets, interpreting results, and improving model performance. You will also learn why concepts like overfitting, generalization, and feature selection are critical when developing reliable predictive systems.
Whether you are a complete beginner, a student, an aspiring data scientist, or a developer looking to enter the field of artificial intelligence, this course offers a structured path to mastering the fundamentals of machine learning, mathematics, and Python through practical application. Throughout the course, you will implement 11 core machine learning algorithms from scratch, validate them using *scikit-learn*, learn to interpret the mathematical notation found in research papers, build *gradient descent* and *backpropagation* manually, and complete 14 real-world projects—including 3 comprehensive end-to-end capstone projects. This path provides you with a deep, practical understanding of how these concepts are applied in real-world scenarios, preparing you to build and debug professional machine learning models.
What you will learn in ML from Zero: Machine Learning Math & Python from Scratch:
- Derive and implement 11 core ML algorithms from scratch in pure Python and NumPy.
- Prove your implementations are correct by validating them against scikit-learn.
- Read the mathematical notation used in ML papers with confidence.
- Build gradient descent, backpropagation and PCA by hand, from the chain rule up.
- Complete 14 real-dataset projects, including 3 full end-to-end capstones.
- and …
Course specifications
Publisher: Udemy
Instructors: Vaibhav Kumar Singh
Language: English
Level: Introductory to Advanced
Number of Lessons: 66
Duration: 6 hours and 34 minutes
Course topics
ML from Zero: Machine Learning Math & Python from Scratch Prerequisites
Basic Python: functions, loops, lists. That’s genuinely it.
No calculus or linear algebra required – Section 2 builds every piece of math the course uses, from nothing
A laptop. No GPU, no cloud account, no paid services
Pictures
ML from Zero: Machine Learning Math & Python from Scratch introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
833 MB