Introduction to Deep Neural Networks Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling or clustering raw…

原文:written by Sebastian Raschka on March 14, 2015 中文版译文:伯乐在线 - atmanic 翻译,toolate 校稿 This article offers a brief glimpse of the history and basic concepts of machine learning. We will take a look at the first algorithmically described neural network…

人类通过模仿自然界中的生物,已经发明了很多东西,比如飞机,就是模仿鸟翼,但最终,这些东西会和原来的东西有些许差异,artificial neural networks (ANNs)就是模仿动物大脑的神经网络. ANNs是Deep Learning的基本组成部分,它有很多用处: ANNs are at the very core of Deep Learning. They are versatile, powerful, and scala‐ ble, making them ideal to…

一.Training of a Single-Layer Neural Network 1 Delta Rule Consider a single-layer neural network, as shown in Figure 2-11. In the figure, d i is the correct output of the output node i. Long story short, the delta rule adjusts the weight as the follow…

Planar data classification with a hidden layer Welcome to the second programming exercise of the deep learning specialization. In this notebook you will generate red and blue points to form a flower. You will then fit a neural network to correctly cl…

LSTM 可视化 Visualizing Layer Representations in Neural Networks Visualizing and interpreting representations learned by machine learning / deep learning algorithms is pretty interesting! As the saying goes — “A picture is worth a thousand words”, the s…

neurons and simple neural networks pynest – nest模拟器的界面 神经模拟工具(NEST:www.nest-initiative.org)专为仿真点神经元的大型异构网络而设计. 它是根据GPL许可证发布的开源软件. 该模拟器带有Python的接口[4]. 图1说明了用户的模拟脚本(mysimulation.py)和NEST模拟器之间的交互. [2]包含该接口实现的技术详细描述,本文的部分内容均基于此参考. 仿真内核使用C ++编写,以获得最高性能的仿真…

When a golf player is first learning to play golf, they usually spend most of their time developing a basic swing. Only gradually do they develop other shots, learning to chip, draw and fade the ball, building on and modifying their basic swing. In a…

Note This section assumes the reader has already read through Classifying MNIST digits using Logistic Regression and Multilayer Perceptron. Additionally, it uses the following new Theano functions and concepts: T.tanh, shared variables, basic arithme…

About this Course This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good res…