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Classification Analysis (Coursera)

The "Classification Analysis" course provides you with a comprehensive understanding of one of the fundamental supervised learning methods, classification. You will explore various classifiers, including KNN, decision tree, support vector machine, naive bayes, and logistic regression, and learn how to evaluate their performance. Through tutorials and engaging case studies, [...]

Introduction to Machine Learning: Supervised Learning (Coursera)

In this course, you’ll be learning various supervised ML algorithms and prediction tasks applied to different data. You’ll learn when to use which model and why, and how to improve the model performances. We will cover models such as linear and logistic regression, KNN, Decision trees and ensembling methods [...]

Trees, SVM and Unsupervised Learning (Coursera)

"Trees, SVM and Unsupervised Learning" is designed to provide working professionals with a solid foundation in support vector machines, neural networks, decision trees, and XG boost. Through in-depth instruction and practical hands-on experience, you will learn how to build powerful predictive models using these techniques and understand the advantages [...]

Machine Learning Models in Science (Coursera)

Mar 25th 2024
Machine Learning Models in Science (Coursera)
Course Auditing
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This course is aimed at anyone interested in applying machine learning techniques to scientific problems. In this course, we'll learn about the complete machine learning pipeline, from reading in, cleaning, and transforming data to running basic and advanced machine learning algorithms. We'll start with data preprocessing techniques, such as [...]
Mar 25th 2024
Course Auditing
33.00 EUR/month

Build Decision Trees, SVMs, and Artificial Neural Networks (Coursera)

Mar 25th 2024
Build Decision Trees, SVMs, and Artificial Neural Networks (Coursera)
Course Auditing
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There are numerous types of machine learning algorithms, each of which has certain characteristics that might make it more or less suitable for solving a particular problem. Decision trees and support-vector machines (SVMs) are two examples of algorithms that can both solve regression and classification problems, but which have [...]

Machine Learning Algorithms: Supervised Learning Tip to Tail (Coursera)

This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest neighbours and support vector machines are optimally used. Learners will also gain skills to contrast [...]

Machine Learning: Concepts and Applications (Coursera)

Mar 11th 2024
Machine Learning: Concepts and Applications (Coursera)
Course Auditing
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This course gives you a comprehensive introduction to both the theory and practice of machine learning. You will learn to use Python along with industry-standard libraries and tools, including Pandas, Scikit-learn, and Tensorflow, to ingest, explore, and prepare data for modeling and then train and evaluate models using a [...]

AI skills for Engineers: Supervised Machine Learning (edX)

Learn the fundamentals of machine learning to help you correctly apply various classification and regression machine learning algorithms to real-life problems using the Python toolbox scikit-learn. Machine learning classification and regression techniques have potential uses in various engineering disciplines. These machine learning models allow you to make predictions for [...]

Machine Learning (Coursera)

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably [...]

Business Intelligence (EMMA)

A self-managed MOOC where you organize your own study schedule and learning journey (through the content provided). The amount of data generated by the information society is growing day by day, and will continue to grow thanks to the explosion of social networks, the smarts cities, the big data, [...]