实用机器学习

Neural Networks and Learning Machines

For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hybridized to perform improved learning tasks beyond the capability of either independently.

Neural-Networks-源码.rar

Neural-Networks-源码.rar

Neural_Networks.rar_源码

很好的神经网络例题，附有相应的源代码C++程序，值得一看啊！

Neural Networks and Deep Learning

Michael Nielsen's book,Neural networks, a beautiful biologically-inspired，programming paradigm which enables a computer to learn from observational data

Neural Networks and Learning Machines Third Edition 3rd

類神經網路經典本 Neural Networks and Learning Machines Third Edition 3rd 英文版

Neural Networks and Learning Machines 3rd Edition

有了一定的基础之后学习神经网络的经典书籍。

neural networks and deep learning --michael nielsen

michael nielsen 的neural networks and deep learning ,very nice!

Hands－On.Machine.Learning.with.Scikit－Learn.and.TensorFlow.2017

Part II, Neural Networks and Deep Learning, covers the following topics: What are neural nets? What are they good for? Building and training neural nets using TensorFlow. The most important neural ...

Deep.Learning.with.TensorFlow

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide About This Book Learn how to implement ...

Pattern Recognition Using Neural and Functional Networks

often the terminology does not sound like it’s talking about machines. The activities of this computing sound more human than mechanistic as people speak of machines that behave, react, self-...

Deep.Learning.Made.Easy.with.R.A.Gentle.Introduction.For.Data.Science

A book for everyone interested in machine learning, predictive analytic techniques, neural networks and decision science. Start building smarter models today using R! Buy the book today. Your next ...

Machine.Learning.for.Adaptive.Many-Core.Machines.331

In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume...

电子书Information Theory Inference and Learning Algorithms

44 Supervised Learning in Multilayer Networks . . . . . . . . . 527 45 Gaussian Processes . . . . . . . . . . . . . . . . . . . . . . 535 46 Deconvolution . . . . . . . . . . . . . . . . . . . . . . ....

Convolutional Neural Networks in Visual Computing_A Concise Guide-CRC(2018).pdf

Chapter 2 introduces the concepts of regression, learning machines, and optimization. is chapter begins with an introduction to super- vised learning. e rst learning machine introduced is the linear ...

Deep Learning in Neural Networks

深度学习介绍

Deep Learning in Neural Networks: An Overview

《Deep Learning in Neural Networks: An Overview》深度学习deep learning原版论文

Neural Networks on C#.rar

神经网络算法及案例 winform窗体编程 可以用于研究神经网络算法！

Deep Learning with TensorFlow: Explore neural networks with Python

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide About This BookLearn how to implement ...

The Elements of Statistical Learning

11. Neural Networks 12. Support Vector Machines and Flexible Discriminants 13. Prototype Methods Nearest-Neighbors 14. Unsupervised Learning 15. Random Forests 16. Ensemble Learning 17. Undirected ...

深度学习神经网络(英文版PDF教程）

I Applied Math and Machine Learning Basics 27 2 Linear Algebra 29 2.1 Scalars, Vectors, Matrices and Tensors . . . . . . . . . . . . . . . 29 2.2 Multiplying Matrices and Vectors . . . . . . . . . . ....

Hands_On_Machine_Learning_with_Scikit_Learn_and_TensorFlow book and code

What is Machine Learning? What problems does it try to solve? What are the main categories and fundamental concepts of Machine ...• Scaling neural networks for huge datasets. • Reinforcement learning.

python大作业 含爬虫、数据可视化、地图、报告、及源码（整和为一个文件）（2014-2020全国各地区原油加工量）.rar

（含源码及报告）本程序分析了自2014年到2020年每年我国原油加工的产量，并且分析了2019年全国各地区原油加工量，含饼状图，柱状图，折线图，数据在地图上显示。运行本程序需要requests、bs4、csv、pandas、matplotlib、pyecharts库的支持，如果缺少某库请自行安装后再运行。文件含2个excel表，4个csv文件以及一个名字为render的html文件（需要用浏览器打开），直观的数据处理部分是图片以及html文件，数据处理的是excel文件。不懂可以扫文件中二维码在微信里面问。

仿真电路以及操作方法

用一片通用四运放芯片LM324组成电路，实现以下功能：用低频信号源产生ui1=0.1sin2πft（V），f=500Hz的正弦波信号，加至加法器的输入端，加法器的另输入端加入有自制振荡器产生的信号uo1。要求加法器的输出电压ui2=10 ui1+ uo1。ui2经选频滤波器滤除uo1频率分量，选出f信号为uo2，uo2为峰峰值等于9V的正弦信号。uo2信号经比较器后在1KΩ负载上得到峰峰值2V的输出电压uo3。用NI Multisim 打开即可，参数已调好。对应博客：https://blog.csdn.net/weixin_43723423/article/details/90761331