Awesome-Lists: 📚 Guide to Galaxy, curated, worthy and up-to-date links/reading list for ITCS-Coding/Algorithm/SoftwareArchitecture/AI. 💫 ITCS-编程/算法/软件架构/人工智能等领域的文章/书籍/资料/项目链接精选。 Awesome-CS-Books: 📚 Awesome CS Books/Series(.pdf by git lfs) Warehouse for ...
近年来,深度学习(Deep Learning)和强化学习(Reinforcement Learning)的结合为AI带来了性的突破。这种结合不仅提升了AI系统的表现,还扩展了其应用范围,影响了从图像识别到自然语言处理等多个领域。 1. 深度学习的突破 1. Breakthroughs in Deep Learning 1.1 深度神经网络(Deep Neural Networks, DNNs) Deep Neural Netw...
这三个点是Deep Learning Algorithm的精髓,我在上一篇文章中也有讲到,其中第三部分:Learning Features Hierachy & Sparse DBN就讲了如何运用Sparse DBN进行feature学习。 4. Deep Learning 经典阅读材料: The monograph or review paperLearning Deep Architectures for AI(Foundations & Trends in Machine Learning, 2009...
2.5 指数加权平均的偏差修正(Bias correction in exponentially weighted averages) 2.6 momentum梯度下降(Gradient descent with momentum) 2.7 RMSprop——root mean square prop(RMSprop) 2.8 Adam优化算法(Adam optimization algorithm) 2.9 学习率衰减(Learning rate decay) 2.10 局部最优问题(The problem of local o...
Deep Learning是机器学习中一个非常接近AI的领域,其动机在于建立、模拟人脑进行分析学习的神经网络,近期研究了机器学习中一些深度学习的相关知识,本文给出一些非常实用的资料和心得。 Key Words:有监督学习与无监督学习。分类、回归。密度预计、聚类,深度学习,Sparse DBN, ...
第一周:深度学习的实用层面(Practical aspects of Deep Learning) 1.1 训练,验证,测试集(Train / Dev / Test sets) 1.2 偏差,方差(Bias /Variance) 1.3 机器学习基础(Basic Recipe for Machine Learning) 1.4 正则化(Regularization) 1.5 为什么正则化有利于预防过拟合呢?(Why regularization reduces overfitting?)...
3. Structuring Machine Learning Projects 结构化机器学习项目 本文使用Zhihu On VSCode创作并发布 ML strategy Chain of assumptions in ML fit training set well fit dev set well fit test set well peforms well in real world Single number eva… ...
《DeepLearning.ai 深度学习笔记》发布,黄海广博士整理,深度学习入门首推课程就是吴恩达的深度学习专项课程系列的5门课。该专项课程最大的特色就是内容全面
Deep learning is a type of machine learning (ML) and artificial intelligence (AI) that trains computers to learn from extensive data sets in a way that simulates human cognitive processes. Deep learning models can be taught to perform classification tasks and recognize patterns in photos, text,...
DeeplearningisoneofthemostpopulardomainsintheAIspace,allowingyoutodevelopmulti-layeredmodelsofvaryingcomplexities.Thisbookintroducesyoutopopulardeeplearningalgorithms—frombasictoadvanced—andshowsyouhowtoimplementthemfromscratchusingTensorFlow.Throughoutthebook,youwillgaininsightsintoeachalgorithm,themathematicalprinciples...