TARS (Totally Awesome Robot Servant) - Artificially intelligent robot from Christopher Nolan's Interstellar
A journey into the land of artificial intelligence and machine learning, covering all sorts of algorithms and concepts. This repo contains work done with popular packages and libraries like SciKit-Learn and Tensorflow as well implementing popular machine learning algorithms from scratch.
Based on an extensive YouTube tutorial series by the one and only Sentdex.
Notebooks and code snippets related to videos of the same topic have been grouped into special directories. Below you can find a short index of what can be found in each folder.
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Linear Regression (2 - 12) - Linear Regression implemented with SciKit-Learn and from scratch to better understand its inner workings, Videos 2 to 12 from playlist above.
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K Nearest Neighbors (13 - 19) - K Nearest Neighbors intuition and implementation from scratch and with SciKit-Learn, Videos 13 to 19 from playlist above.
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Support Vector Machine (20 - 33) - Support Vector Machine intuition and scratch implementation, Videos 20 to 33 from playlist above.
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K Means (34 - 38) - The first unsupervised algorithm in the series implemented with popular libraries as well as from scratch, Videos 34 to 38 from playlist above.
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Mean Shift (39 - 42) - A dive into the Mean Shift algorithm with packages and implementation from scratch, Videos 39 to 42 from playlist above.
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Deep Learning (43 - 58) - Implementing Deep Learning models with Tensorflow, Videos 43 to 58 from playlist above.
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OpenAI (59 - 62) - Implementing a neural net and teaching it to play the CartPole Game from OpenAI Gym, Videos 59 to 62 from playlist above.
While the tutorial series is pretty old and not up-to-date on the latest technology anymore, it thought me many concepts and principles that are still valid and introduced me to a topic that is now a big part of my life.
