I’ve been into machine learning for a long time, but never really tried to actually make a neural network from scratch (using Python and Numpy) until the machine learning class I took last semester made me do it for an assignment. I thought the process was pretty illuminating, so I decided to do it again, but this time with some slight changes in my implementation. The goal of the project was to write a basic neural network that could fit sinusoidal data. Nothing complex, so it wouldn’t take too long. This isn't a tutorial but I think you'll still gain some useful information and definitely some entertainment value from this video. Also, the neural network isn't COMPLETELY from scratch, I use numpy, but that's just for matrix multiplication.
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I just finished my first year at Georgia Tech majoring in Computer Science. On this channel, I make videos related to machine learning and programming, lifestyle vlogs, productivity tip videos, and more! If you're interested in that, be sure to hit the subscribe button and leave a like on this video! Subscribe here: http://youtube.com/c/SiddhantDubey/?s...
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00:00 Intro
00:29 Development!
06:51 Conclusion + Outro