Machine Learning

This course is an introduction to sequential decision making and reinforcement learning. We start with a discussion of utility theory to learn how preferences can be represented and modeled for decision making. We first model simple decision problems as multi-armed bandit problems in and discuss several approaches to evaluate [...]

In this course, you will discover how to solve business problems with machine learning, no coding required. You will explore Amazon SageMaker Canvas, a visual point-and-click interface that allows you to generate accurate ML predictions without requiring any machine learning experience or having to write a single line of [...]

In this MOOC, you will be introduced to advanced machine learning and natural language processing techniques to parse and extract information from unstructured text documents in healthcare, such as clinical notes, radiology reports, and discharge summaries. Whether you are an aspiring data scientist or an early or mid-career professional [...]

This course covers the most neglected yet critical skills in machine learning, four vital techniques that are very rarely covered – most courses and books omit them entirely.

This course will complete the GPU specialization, focusing on the leading libraries distributed as part of the CUDA Toolkit. Students will learn how to use CuFFT, and linear algebra libraries to perform complex mathematical computations. The Thrust library’s capabilities in representing common data structures and associated algorithms will be [...]

Nossas boas-vindas ao Curso Fundamentos de IA Aplicados ao CRM. Neste curso, você aprenderá que, conforme a nova economia avança, o mercado se torna mais dependente da coleta, estruturação e análise de dados. Por isso, decisões baseadas em dados têm se tornado tão importantes para companhias que querem [...]

In this course you will: understand the naïve Bayesian algorithm; understand the Support Vector Machine algorithm; understand the Decision Tree algorithm; understand the Clustering. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional [...]

In this course, you will: understand the basic concepts of machine learning; understand a typical memory-based method, the K nearest neighbor method; understand linear regression; understand model analysis. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional [...]

Este curso te brindará los conocimientos necesarios para la implementación de algoritmos de NLP. Mediante el uso de los últimos algoritmos más populares en NLP se procederá a dar solución a un conjunto de problemas propios del área. Para realizar este curso es necesario contar con conocimientos de programación [...]

This course will introduce the concepts of interpretability and explainability in machine learning applications. The learner will understand the difference between global, local, model-agnostic and model-specific explanations. State-of-the-art explainability methods such as Permutation Feature Importance (PFI), Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanation (SHAP) are explained and [...]