In our latest of clubs where we geek out hard in our quest to better understand machines to make sure they don't control us too soon, we're going to talk about how they see. Facial recognition is very much here, let's learn about and discuss how it works._x000D_ _x000D_ So, how do machines see? How does it compare to how we see? How do they actually recognize images? And what in the matrix is the "convolutional neural network"? _x000D_ _x000D_ In the past, image recognition is an area in which machines constantly failed... Until we leveraged neural networks to do the job and, once again, revolutionize technology. In 2012, AlexNet achieved so much attention that it brought on the deep learning era which is still thriving loudly today. Let's do some deep learning of our own and let's have an intelligent and fascinating discussion! Let's look into the convolutional idea and the mechanics of how machines see._x000D_ _x000D_ 在我们最近的活动中，我们努力探索更好地理解机器，以确保它们不会过早地控制我们，我们将讨论它们是如何看见周围的。面部识别在这里非常重要，让我们来学习和讨论它是如何工作的。_x000D_ _x000D_ 那么，机器是怎么看东西的呢?它和我们看到的相比如何?它们是如何识别图像的?矩阵中的什么是“卷积神经网络”?_x000D_ _x000D_ 在过去，机器图像识别是一个经常失败的领域。直到我们利用神经网络来完成这项工作，再一次彻底改变技术。2012年，AlexNet获得了如此多的关注，它带来了深度学习时代，今天仍然在蓬勃发展。让我们自己做一些深入的学习，让我们来一个聪明而有趣的讨论!让我们来看看卷积的思想和机器图像识别的机制。