highly folded data manifolds. At this point, you should have a pretty good intuition as to why deep learning excels this: it takes the approach of incrementally decomposing a complicated geometric transformation into a long chain of elementary ones, which is pretty much a strategy...
x += step * grad_valuesreturnx# 在多个连续尺度上运行梯度上升# 梯度上升的步长step =0.01# 运行梯度上升的尺度个数num_octave =3# 两个尺度之间的大小比例octave_scale =1.4iterations =20# 如果损失增大到大于 10,我们要中断梯度上升过程,以避免得到丑陋的伪影max_loss =10.base_image_path ='img_url'i...
The application field of 3D deep learning has snowballed in recent years. We have superb applications in various areas, including robotics, autonomous driving & mapping, medical imaging, and entertainment. When we look at the results, we are often awed (but not all the time 😁), and we m...
# GRADED FUNCTION: conv_single_stepdefconv_single_step(a_slice_prev,W,b):"""Apply one filter defined by parameters W on a single slice (a_slice_prev) of the output activationof the previous layer.Arguments:a_slice_prev -- slice of input data of shape (f, f, n_C_prev)W --...
Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide" - dvgodoy/PyTorchStepByStep
Deep learning is the most interesting and powerful machine learning technique right now. TensorFlow 2 is one of the top deep learning libraries in the Python ecosystem. With Keras, you can easily tap into the power of deep learning in just a few lines of code. These are the best-of-breed...
11.5 Beyond text classification: Sequence-to-sequence learning 11.5.1 A machine translation example 11.5.2 Sequence-to-sequence learning with RNNs 11.5.3 Sequence-to-sequence learning with Transformer Summary 后记 写在前面,本文是阅读python深度学习第二版的读书笔记,仅用于个人学习使用。另外,截至2022年3...
Deep learning with Python 学习笔记(4) 本节讲卷积神经网络的可视化 三种方法 可视化卷积神经网络的中间输出(中间激活) 有助于理解卷积神经网络连续的层如何对输入进行变换,也有助于初步了解卷积神经网络每个过滤器的含义 可视化卷积神经网络的过滤器 有助于精确理解卷积神经网络中每个过滤器容易接受的视觉模式或视觉...
git clone https://github.com/yuxuan-lou/Step-by-Step-ViT-training-on-Cifar10-with-Colossal-AI....
Neural Networks and Deep Learning(week4)Building your Deep Neural Network: Step by Step,程序员大本营,技术文章内容聚合第一站。