C++ Machine Learning Tutorial Part 1 - Extract, Transform, Load (ETL)

C++ Machine Learning Tutorial Part 1 includes implementation of necessary data containers and structures that will be used in future videos.

We build a data container class that holds the transformed MNIST Handwriting data. We also implement a data handler that will extract, and transform the data to be useable by future algorithm implementations.

Bugs aren't edited out so everyone can learn :)

[randomrandom]

Finally ! I've been searching for so long a tutorial that actually shows you how to code a neural network, not just "hey use this already built black box and hope for the best". I dont mind using the black box once I understand how its made, but I'll never learn if I never try for myself.

[gerardonfiya]

The 3rd part in the Deep Learning sub-series is dropping Friday! I hope you all enjoy it!

[IITD]

It's heartbreaking how such good content is so under rated but I am always with you! Keep up the good work

[andrewm]

Oh, this seems really interesting. Have been trying to learn some c for ml in a sort of practical way and not found as much material so this looks really useful. Thanks.

[sigtermki]

Incredible. Been looking for good implementations from pure STL perspective. Great work!

[mockingbird]

Thank you so much for making videos in C++ . Im loving it!

[IdeasAndLife]

Please continue more such videos in C++. It is very informative and I have found it highly useful.Please continue to keep the good work up.

[benbrown]

Not me watching this at 1:30am and getting blinded every time he switched to the MNIST documentation

[anuj]

O My Goodness
I was waiting for this for a while
Thank You is not enough for what u did

[josephpark]

If some people are having trouble reading from file, I changed fopen(path.c_str(), "r"); to fopen(path.c_str(), "rb"); to make the File specifically read bytes. The code started working after that. In case anyone else has the same problem, you can try this. I'm not sure what causes this, probably changes in the language over time.

[silverdogface]

This is great thank you! please continue making videos

[skiskyscrystal]

bro i search soo much for this ty for making this video you are the best

[adilahmed]

I didn't understand 1 byte of information but seeing you do it so skillfully was entertaining loved it 😭😭😭😭

[conanprod.]

This is so brilliant! Actually, I was looking for Mask R-CNN C++ implementation for my course work. I've started from the beginning and looked for how to implement any CNN on C++ just too look at the structure and found your tutorials. Helps a lot. Thank you from Russia! By the way, do you know any resources with detailed description of Mask R-CNN model (like a number of neurons and layers for the net, I can't find it)?

[manodeepray]

i have been looking for such a playlist to learn the inner working of the ml blackboxes ..hopefully it gives me what i need

[MCroppered]

Great video! I’m looking forward to watching the rest of the series. Side point: that keyboard has such a nice sound to it. What are you using?

[OmarSamirz]

Thank you for this fantastic series! I'm eagerly looking forward to seeing supervised algorithms, gradient descent and others. Additionally, could you recommend the best sources for learning to write Makefiles?

[findervlogs]

Nice explanation! Could you please create a video on reinforcement learning using c++?

[xyz]

#include <iostream>

int main() {
std::cout << " Thankyou !"; return 0;
}

Edit: oh and stay home and stay safe.😀

[TravelingMooseMedia]

Wait I think you're my new favorite youtuber