Neural Networks

After completing this course, learners will be able to: analytically optimize different types of functions commonly used in machine learning using properties of derivatives and gradients; approximately optimize different types of functions commonly used in machine learning using first-order (gradient descent) and second-order (Newton’s method) iterative methods; visually interpret [...]

In the second course of the Machine Learning Specialization, you will: build and train a neural network with TensorFlow to perform multi-class classification; apply best practices for machine learning development so that your models generalize to data and tasks in the real world; build and use decision trees and [...]

Just as teachers help students gain new skills, the same is true of artificial intelligence (AI). Machine learning algorithms can adapt and change, much like the learning process itself. Using the machine teaching paradigm, a subject matter expert (SME) can teach AI to improve and optimize a variety of [...]

This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well [...]

The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image shown. This course focuses on the all-important problem of perception. We first describe the problem of tracking objects in complex scenes. We look at two key challenges in this context. The [...]

IA não é apenas para engenheiros. Se quiser que sua organização se torne melhor no uso de IA, este é o curso que todos, especialmente aos seus colegas não técnicos, devem fazer.

In this course, we will build on our knowledge of basic models and explore advanced AI techniques. We’ll start with a deep dive into neural networks, building our knowledge from the ground up by examining the structure and properties. Then we’ll code some simple neural network models and learn [...]

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 [...]