Nice video, keep going! On the next step, gradients will be small, [-0.12, 0.1, -0.001], so we won't get a large improvement. The weights after the next step will be [0.574, -2.302, 2.927], and NLL here equals 0.0476, which is again smaller than the previous one (0.0486). Step: 0, NLL: 0.5707 W = [1.0000, -2.0000, 3.0000] grad = [4.3791, 2.9224, 0.7301] Step: 1, NLL: 0.0486 W = [0.5621, -2.2922, 2.9270] grad = [-0.1198, 0.1043, -0.0016] Step: 2, NLL: 0.0476 W = [0.5741, -2.3027, 2.9271] grad = [-0.0801, 0.1181, 0.0038] ... (a few hundreds of steps later) Step:999, NLL: 0.0024 W = [1.4923, -4.3960, 2.8096] grad = [-0.0029, 0.0067, 0.0004]
@howithinkabout
2 ай бұрын
@@mie5953 🙌 incredible work!!
@jakesimonds5051
3 ай бұрын
These videos are fantastic. Your pacing is (for me at least) excellent, the illustrations are awesome, and you're doing a fantastic job of job of motivating everything. Keep it up!!!!!
@howithinkabout
3 ай бұрын
So glad to hear it! Thanks for the kind and encouraging words :) I'll do my best!
@frannydonington9925
3 ай бұрын
Another great video!! Such good quality explanations. A really great study tool :)
@howithinkabout
3 ай бұрын
thank you so much!! 🙏
@stunks6147
2 ай бұрын
Excited to see how you explain neural networks! Keep up the good work!
@howithinkabout
2 ай бұрын
Thank you! Part 3 will be out next (hopefully in the next week) and right after that will be a neural network series
@ssingh7317
3 ай бұрын
Keep this Machine Learning concepts series videos :)
@howithinkabout
3 ай бұрын
I got big plans for this channel :) but let me know what you would like to learn about!
@ssingh7317
3 ай бұрын
@@howithinkabout I would love to watch mathematics for better understanding of algorithms.
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