CV+Deep Learning——网络架构Pytorch复现系列——classification(一:LeNet5,VGG,AlexNet,ResNet) 引言此系列重点在于复现计算机视觉(分类、目标检测、语义分割)中深度学习各个经典的网络模型,以便初学者使用(浅入深出)! 代码都运行无误!! 首先复现深度学习的经典分类网络模块,其中专门做目标检测的Backbone(10.,11.)...
06年后,大批deep learning文章涌现,感兴趣的可以看下大牛Yoshua Bengio的综述Learning deep architectures for {AI},不过本文很长,很长…… 5. Deep Learning工具——Theano Theano是deep learning的Python库,要求首先熟悉Python语言和numpy,建议读者先看Theano basic tutorial,然后按照Getting Started下载相关数据并用gradi...
RBM是构建deep learning 的基础,之前研究了一段时间,把相关的理论进行了下系统的梳理,并进行了总结。理论总结以pdf上传到了这里: https://files.cnblogs.com/HarryJiang/rbm.pdf 相关的单机版python实现代码: https://github.com/nebuladream/sparse_class_rbm/tree/master/ClassRBMPy...
感兴趣的能够看下大牛Yoshua Bengio的综述Learning deep architectures for {AI},只是本文非常长,非常长…… 5. Deep Learning工具—— Theano Theano是deep learning的Python库,要求首先熟悉Python语言和numpy,建议读者先看Theano basic tutorial,然后依照...
python实现比较简单: W1=W1-learning_rate*dW1b1=b1-learning_rate*db1W2=W2-learning_rate*dW2b2=b2-learning_rate*db2 至此,已经完成了主要的工作,一个完整的神经网络已经搭建完成。 但是还有一个问题,迭代! 如果我们只优化一次参数是远远不够的,我们需要进行大量的迭代,也就是不断的完成“前向传播->后向传...
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...
Applied Deep Learning with Python是Alex Galea Luis Capelo创作的计算机网络类小说,QQ阅读提供Applied Deep Learning with Python部分章节免费在线阅读,此外还提供Applied Deep Learning with Python全本在线阅读。
《Google Turns To Deep Learning Classification To Fight Web Spam》 介绍:Google用Deep Learning做的antispam(反垃圾邮件) 《NLP常用信息资源》 介绍:NLP常用信息资源* 《NLP常用信息资源》 《机器学习速查表》 介绍:机器学习速查表 《Best Papers vs. Top Cited Papers in Computer Science》 介绍:从...
- Hands-On Machine Learning with Scikit-Learn and TensorFlow by Aurélien Géron 3. 论文: - ImageNet Classification with Deep Convolutional Neural Networks by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton - Generative Adversarial Nets by Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing...
Chapter 4: Getting started with neural networks: classification and regression Chapter 5: Fundamentals of machine learning Chapter 7: Working with Keras: a deep dive Chapter 8: Introduction to deep learning for computer vision Chapter 9: Advanced deep learning for computer vision Part 1: Image se...