Gradient descent optimization in C++ - Part 2 - The code скачать в хорошем качестве

Gradient descent optimization in C++ - Part 2 - The code

Gradient descent optimization in C++ - Part 2 - The code Gradient descent is a powerful numerical optimization technique that is used in many fields such as machine learning and image registration, indeed anywhere where we need to find a set of parameters that minimizes the output of an unknown function. In part 2 of this two-part series I focus on how to implement the gradient descent algorithm in C++. If you haven't seen part 1, then you can check it out here:    • Gradient descent optimization in C++ - Par...   The code described in this video can be found on the QuantitativeBytes GitHub repository at: https://github.com/QuantitativeBytes/... ********************************** You can also follow me on the QuantitativeBytes Facebook page at: www.facebook.com/QuantitativeBytes ********************************** As with all of my videos, I show the code that I have developed to solve the particular problems that I need to solve, with the hope that it may provide sufficient background and inspiration to allow you to go on to develop your own code if you wish to. My code may not be the most appropriate solution to the problem you are trying to solve, so I urge you to consider the problem carefully and decide for yourself on the most appropriate solution. I make every effort to ensure that my code works as it should and is free of bugs, but of course I cannot provide any guarantees. If you use my code as shown, I strongly encourage you to make sure that you test it thoroughly to ensure that it works as you need it to. If you find a bug, do please let me know in the comments!