Ahmed Gad is a data neuroscientist who is passionate about artificial intelligence, machine learning, deep learning, computer vision, and Python with over 7 projects in the fields. He is a researcher at the University of Ottawa, Canada. He has contributed to over 80 original articles and additional tutorials in addition to his 4 books. He hopes to continue adding value to the neural data science community by sharing his writings, recorded tutorials, and consultation with new trainees in the field.
Thank you! The PDF is available here: www.slideshare.net/slideshow/introduction-to-artificial-neural-network-stepbystep-training-testing-example/75507051
@@AhmedGadd الفكرة حضرتك أن انا مش خريج حاسبات ومعلومات الماتلاب هو اللي اعرفه علشان ده اللي درسته في الكلية وأنا معرفش البايثون وحاولت افهمه بس معرفتش
Thank you for this video which explains the NSGAII very well, I was not able to understand before despite the different sites and videos that I saw. I have a question, I would like to apply the NSGAII for a problem of placing equipment for which I have dimensions (lengths, widths) on a surface for which I also have the dimension. My goal is to have different combinations of equipment inside the surface. I have as constraint that the equipment does not overlap and that they are all inside the surface. Once I have defined my objective functions and apply the algorithm, how can I visually represent the different equipment placed on the predefined serface? I can't really visualize how this algorithm can provide me differents combinations since NSGA2 is the most popular algorithm in placement problems. Thanks for your help !
بارك الله بيك استاذ وشكرا على جهودك الجبارة لكن لدي استفسار هل لاحظت البارشيل لاخر وزنين 3 و4 من اشتقيت يمكن الاشتقاق كان خطأ لان اشتقيت x وبقيت الوزن مع العلم احنا عنشتق بالنسبة للوزن وشكرأ جزيلا على شرحك الاكثر من ممتاز
It's amazing how the community can take previous work and adapt it in unexpected ways. Fantastic video and great work by PyGAD and Tikitikitikidesuka 👍
Sir, the solution G is better in the Feedback than the solution H, E and B. Because the Feedback of G is 4.0 but the others solutions are 4.6, 4.5 and 4.4. So, the solution G is also in the front 2.
Thanks for your comment! But solution G cannot be part of Front 2 because solution C dominates it. Solution C is better than solution G in all the objectives. Note that all the objective functions are minimization. For Cost, solution C has 65 which is better than 80 for G. For Feedback, solution C has 3.5 which is better than 4.5 for G. As solution C is better than solution G in all the objective functions, this means solution C dominates solution G. Thus, solution G cannot be part of Front 2.
hello. I am trying a similar model. but I have the problem that it takes too long to train. does not use the GPU. It is only using the Google colab cpu. I have the GPU activated but nothing.
يا دكاور بعد اذنك دي طريقه تعتبر كلام فارغ يعني مثلا لو عندي داتا ماخدها من كنترولر معين وعملت بناء للنيورل نتوورك ساعتها مش هستفيد حاجه غير اني جبت رسبونس زي الريسبونس اللي خدت منه الداتا يبقى انا استفدت ايه ؟
J'espère que vous pourrez m'aider dans mon sujet sur la prévision de la consommation d'énergie. J'ai beaucoup de données et je n'ai pas compris ce qui a été choisi comme entrée et sortie, et comment puis-je inclure la date dans une demande ? Merci ❣️
