Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, ...
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, ...
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron English | 2017 | ISBN: 1491962291 | 566 Pages | EPUB | 8.41...
还开始研究一系列开源模型(包括各自对应的模型架构、训练方法、训练数据、本地私有化部署、硬件配置要求、微调等细节)该项目部分一开始是作为此文《》的第4部分,但但随着研究深入 为避免该文篇幅又过长,将把『第...
LLMs之Grok-1:Grok-1的简介、安装、使用方法之详细攻略 目录 Grok-1的简介 Grok-1的安装 ...2024年3月17日(当地时间),马斯克的AI创企xAI重磅发布了Grok-1的基础模型权重和网络架构,这是一款大型语言模型。...
neural-style模型是一个风格迁移的模型,是GitHub上一个超棒的项目,那么什么是风格迁移,我们来举一个简单的例子: 这里,我选择了将梵高的画风和我们的东北大学的工学馆相结合,让工学馆融入了梵高的星空效果图...
Module 3, Large Scale Machine Learning with Python, covers interesting deep learning techniques together with an online method for neural networks. Although TensorFlow is only in its infancy, the ...
5. Transformer-TTS: Neural Speech Synthesis with Transformer Network 文章于2019年1月发表 Transformer-TTS可以看做Tacotron2+transformer的组合,作者认为优点主要为: 通过移除RNN结构实现并行训练,因为...
自然语言处理NLP中的N-gram模型 自然语言处理NLP中的N-gram模型 Naive Bayes N-gram N-gram简介 N-gram中的概率计算 N-gram的用途 用途一:词性标注 用途二:垃圾短信分类 用途三:分词器 ......
Table of Contents Giving Computers the Ability to Learn from Data Training Simple Machine Learning Algorithms for Classification ...Modeling Sequential Data using Recurrent Neural Networks
http://blog.systransoft.com/how-does-neural-machine-translation-work/ In this issue of step-by-step articles, we explain how neural machine translation (NMT) works and compare it wi
subword-nmt干啥用的 解决未登录词问题的一种方法。 在做nlp的时候,很多时候我们会对语料做一个预处理,生成语料的一个字典。为了不让字典太大,我们通常只会把出现频次大于某个阈值的词丢到字典里边,剩下所有的词...
文章作者:Tyan 博客:noahsnail.com  |  CSDN  |  简书 ...声明:作者翻译论文仅为学习,如有侵权请联系作者删除博文,谢谢!...Faster R-CNN: Towards Real-Time ...
Part 1:Python Basics with Numpy (optional assignment) Part 2: Logistic Regression with a Neural Network mindset
被引用 6824 次,又是一篇高引用论文。也是紧跟在seq2seq模型原论文,列表中 [THUNLP-MT (6/10)],后面的一篇论文。本文的重点即为注意力机制,是现今NLP领域中非常重要的机制。
在ORB-SLAM2的基础上进行语义地图的构建。
High-Speed Ship Detection in SAR Images Based on a Grid Convolutional Neural Network Abstract1. Introduction2. Methodology2.1.Dataset2.2 G-CNN2.3. Model2.4. Anchor Box2.5.Evaluation Indicator3. Experi...
@article{DBLP:journals/remotesensing/YaoLFSLMYZ21,author = {Yuan Yao andYee Leung andTung Fung andZhenfeng Shao andJie Lu andDeyu Meng andHanchi Ying andYu Zhou},title = {Continuous Multi-Angle...
%% Machine Learning Online Class - Exercise 4 Neural Network Learning % Instructions % ------------ % % This file contains code that helps you get started on the % linear exercise. You
作者提出之前的工作只考虑了用户的序列表现,但是对用户的主要目的并没有明显地强调,因此作者提出Neural Attentive Recommendation Machine(NARM) 方法 NARM的整体框架如下: 编码器方面含有global encoder和...