Tolshao

摘要： 概述：处理样本数不规则的模型recurrent neural network递归神经网络参数共享,前->后样本逐个扫描a激活用一套参数y激活用一套参数参数流x、y个数不一致的RNN序列样本分类问题音乐生成、机器翻译RNN类型总结language model with RNN输出P(sentence),并按照y(i)展开为字符串从训练模型采样在训练过程中，结局梯度爆炸gradient clippin... 阅读全文

摘要： Face RecognitionIn this assignment, you will build a face recognition system. Many of the ideas presented here are from FaceNet. In lecture, we also talked about DeepFace. Face recognition problems co... 阅读全文

摘要： Autonomous driving - Car detectionWelcome to your week 3 programming assignment. You will learn about object detection using the very powerful YOLO model. Many of the ideas in this notebook are descri... 阅读全文

摘要： Residual NetworksWelcome to the second assignment of this week! You will learn how to build very deep convolutional networks, using Residual Networks (ResNets). In theory, very deep networks can repre... 阅读全文

摘要： Keras tutorial - Emotion Detection in Images of FacesWelcome to the first assignment of week 2. In this assignment, you will:Learn to use Keras, a high-level neural networks API (programming framework... 阅读全文

摘要： Convolutional Neural Networks: ApplicationWelcome to Course 4's second assignment! In this notebook, you will:Implement helper functions that you will use when implementing a TensorFlow modelImplement... 阅读全文

摘要： 根据国际系统工程协会（INCOSE）在 2007 年发布的《SE 愿景 2020》中的定义，MBSE 是建模方法在系统工程中的形式化应用，用以支持在系统全生命周期内开展需求、设计、分析、验证和确认相关的活动。从定义可以看到，MBSE 是基于文档的传统系统工程工作模式的演进，力求以多视角的系统模型做为桥梁，将跨学科/领域的模型关联起来，实现跨学科/领域的模型追溯，从而驱动大型复杂系统生存周期内各阶段... 阅读全文

摘要： Convolutional Neural Networks: Step by StepWelcome to Course 4's first assignment! In this assignment, you will implement convolutional (CONV) and pooling (POOL) layers in numpy, including both forwar... 阅读全文

摘要： 本文转自知乎（Sophia）公众号【计算机视觉联盟】笔记图片由 TessFerrandez 整理，这套信息图优美地记录了深度学习课程的知识与亮点。因此它不仅仅适合初学者了解深度学习，还适合机器学习从业者和研究者复习基本概念。这不仅仅是一份课程笔记，同时还是一套信息图与备忘录。从深度学习基础、卷积网络和循环网络三个方面介绍该笔记1. 深度学习基本概念监督学习：所有输入数据都有确定的对应输出数据，在各... 阅读全文

摘要： Welcome to this week's programming assignment. Until now, you've always used numpy to build neural networks. Now we will step you through a deep learning framework that will allow you to build neural networks more easily. 阅读全文