Tensors & Machine Learning

When it comes to building neural network models, there’s a lot of factors to consider such as hyperparameter tuning, model architecture, whether to use a pre-trained model or not, and so on and so forth. While it’s true that these are all important aspects to consider, I would argue that proper understanding of data representations […]

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From Artificial Intelligence to Deep Learning

Deep learning is one of the hottest topics in today’s digital world. Everyone wants to know just how much potential this tool has in terms of revolutionizing technology and whether or not it will be able to introduce utopian elements such as intelligent autonomous systems (chatbots, self-driving cars, etc.). However, before one delves into the […]

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Predicting Suicide Rates Using Linear Regression

Hi everyone! I’m taking an online deep learning with PyTorch course, which has turned out to be a really enjoyable experience. That being said, for our second assignment, our core focus was on building a Linear Regression model that predicts insurance charges. I sure finished that assignment. However, to spice things up a bit, I […]

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Exploring 5 PyTorch Functions

Hi everyone! I recently discovered a free, live-streamed 6-week PyTorch deep learning course on YouTube and decided to commit to it in the spare time that I have. The following is a copy of the Jupyter Notebook instance I wrote for the first assignment. This notebook can also be found on GitHub here. I hope […]

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NFL Team Ranking Approximation From 1970 – Current

Yesterday was the last day of my semester and a great day to put one of my favorite models, the Massey Method, from linear algebra to good use. As I revisited my linear algebra book to look back at all that we’ve learned through out the semester, the idea of finding out how NFL teams […]

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