Courses in category Machine learning
Showing 1 – 7 of 7 courses
Machine Learning with Spark ML
Learn to use Spark ML for creating scalable machine learning solutions. Practice with regression, classification, feature engineering...
2 hours 7 minutes 29 seconds
The Real-World ML Tutorial
Hello! I am Pau, a machine learning engineer with many years of experience in developing real-world ML products. Do you want to design, develop, and...
4 hours 3 minutes 44 seconds
Machine Learning & Containers on AWS
In this practical course, you will learn how to build a complete data pipeline on the AWS platform - from obtaining data from the Twitter API to analysis, stora
1 hour 33 minutes 34 seconds
Build a Simple Neural Network & Learn Backpropagation
Learn backpropagation and gradient descent by writing a simple neural network from scratch in Python - without libraries, just the basics. Ideal...
4 hours 34 minutes 9 seconds
Data Preparation & Cleaning for ML
Have you ever heard the expression "data preparation and cleaning"? This is perhaps the most important part of the entire machine learning process.
3 hours 7 minutes 23 seconds
Learn to Build Machine Learning Systems That Don't Suck
A live, interactive course that will teach you from scratch how to design, create, and implement ready-to-use ML systems - no fluff and academic...
32 hours 6 minutes 40 seconds
Predictive Analytics & Machine Learning
Predictive analytics and machine learning is a course that will help you master key concepts and practical skills in data forecasting...
55 minutes 15 seconds
Machine learning
Machine Learning (ML) is a key area of artificial intelligence that enables computers to learn from data and make decisions without explicit programming. In this category, you will get acquainted with the basics of ML, various algorithms (linear regression, decision trees, gradient boosting), learning methods (supervised, unsupervised, reinforcement learning), and tools (Scikit-learn, TensorFlow, PyTorch).
You will learn to analyze data, build models, and apply them to real-world tasks—from trend prediction to process automation.