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Machine Learning

Motivations | 2021 | Links:

Machine Learning

ML algorithms provide different solutions to current issues through its three approaches, Supervised learning, Unsupervised learning, and Reinforcement learning.

Materials

  • Deep Learning. Ian Goodfellow, Yoshua Bengio, & Aaron Courville

Notebooks

  • Introduction to Generative Adversarial Networks: Creating a GAN to generate samples of a normal distribution.

Oscar Guarnizo

About

Hi, I’m Oscar Guarnizo, a young computer scientist from Ecuador. My research expertise relies on computer vision and deep learning. I have already worked on projects related to convolutional neural networks (CNN) for classification, segmentation, license plate recognition, and generative adversarial networks. However, I am currently turning towards Reinforcement Learning (RL) research, a mature technology with a solid contextualization and mathematical formulation.

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Other Projects

Mathematics

Mathematics

Mathematics, the fundamental science, allows us to understand the theoretical and practical implementations of any problem deeply. Continue reading Mathematics

Reinforcement Learning

Reinforcement Learning

Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Continue reading Reinforcement Learning


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Oscar Guarnizo

Oscar Guarnizo

Hi there! I’m Oscar, a young computer scientist from Ecuador interested in AI/ML.

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