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Machine Learning 🧠

In this directory I created an artificial intelligence that I learned in the "Minicourse: Introduction to Artificial Intelligence in Python", from UFU - Federal University of Uberlândia. Available in: https://youtu.be/6ly1KKobfOA. This neural network defines whether something is a human or a horse.

Download Dataset: https://storage.googleapis.com/laurencemoroney-blog.appspot.com/horse-or-human.zip

Libraries used 📚

  • TensorFlow: TensorFlow is a complete open source platform for machine learning. It has a comprehensive and flexible ecosystem of tools, libraries, and community resources that enable researchers to advance next-generation ML and developers to build and deploy ML-powered applications.

  • NumPy: NumPy is the foundational package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as arrays and masked arrays), and a variety of routines for quick operations on arrays, including math, logic, shape manipulation, sorting, selection, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.

  • MatPlotLib: Matplotlib is a software library for creating graphs and general data visualizations, made for and from the Python programming language and its NumPy math extension.

  • Keras: Keras is an API designed for humans, not machines. Keras follows best practices to reduce cognitive load: it offers consistent and simple APIs, minimizes the number of user actions required for common use cases, and provides clear, actionable error messages. It also has extensive documentation and developer guides.

About

In this directory I created an artificial intelligence that I learned in the "Minicourse: Introduction to Artificial Intelligence in Python", from UFU - Federal University of Uberlândia

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