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Deep learning就是machine learning的子方法，个人更倾向于把它看成与SVM，decision tree或者进一步random forest，KNN这类传统ml方法并列的一种。21世纪初的时候SVM的爆火使之成为了ml的主要方法，至今SVM和random forest还在很多小样本难以开展deep learning的classification任务中起着至关重要的作用。而当时由于数据量小 ...
深度学习（Deep Learning）话题下的优秀答主 Normalization这个事得好好掰扯掰扯。 上古时期，网络经常在初始几个iteration之后，loss还没下降就不动，必须得把每一层的gradient与weight的比值打印出来，针对性地调整每一层的初始化才能不崩。
Element of Statistical Learning，Machine Learning: A Probability Perspective; Pattern Recognition and Machine Learning , 统计学习方法; Deep Learning，机器学习(周志华) 吴恩达的Coursera课程，Introduction to Statistical Learning; Python Machine Learning，集体编程智慧
深度学习（Deep Learning） 神经网络Linear、FC、FFN、MLP、Dense Layer等区别是什么？ 细分这几个模块叫法的本质区别 显示全部 . 关� ...
在深度探讨machine learning和data science的联系之前，这里简要地讨论一下machine learning 和deep learning。machine learning是一套算法，来训练数据集做预测或者采取行动以使得系统最优化。举例来说，supervised classification algorithms被用来根据历史数据将想要贷款的客户分成预期好的和预期差的(good or bad prospects ...
考研结束后，很多准研一的同学可以准备提前进行相关知识储备了，不要在研一花费大量时间在前期基础知识上，这里给大家推荐一本深度学习入门精选，大神李沐的动手学深度学习（Dive into deep learning），这本书的最大优势是有李沐本人在B站上的讲解，有数学基础知识，每一步实现代码，让你新书 ...
花书可不是入门的书，它默认你对 deep learning 的各个领域都有了基本的了解与涉猎，因此对应于很多知识就删繁就简，不会给你掰开揉碎的讲；相应的去描写更加深入和新颖的理论与方法，可以说是用来进阶与补充的书。再多说一下，花书的作文方式很像是论述类学术论文；没怎么读过论文看起来跟 ...
深度学习（Deep Learning） 想了解CNN最早的原型是什么，是哪篇论文里提的，而后又是有哪些具有重大意义的论文？ 想追一追这些论文看，有朋友知道吗？
深度学习（Deep Learning） 一张v100 32G还是两张4090 24G？ 目前更倾向于两张4090 24g，但v100的32g显存能弥补性能差距吗?两张4090无nvlink大约…
深度学习（Deep Learning） ROCm. 为什么常见的深度学习软件都只支持CUDA，难道AMD显卡不值得用AI吗？ 似乎支持AMD显卡的AI软件不� ...
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