【推荐】Keras教程:Python深度学习超级入门指南
2016-12-02 00:00
786 查看
2016-11-27 机器学习研究会
点击上方“机器学习研究会”可以订阅哦
摘要
转自:爱可可-爱生活
In this step-by-step Keras tutorial, you’ll learn how to build a convolutional neural network in Python!
In fact, we’ll be training a classifier for handwritten digits that boasts over 99% accuracy on the famous MNIST dataset.
Before we begin, we should note that this guide is geared toward beginners who are interested in applied deep learning.
Our goal is to introduce you to one of the most popular and powerful libraries for building neural networks in Python. That means we’ll brush over much of the theory and math, but we’ll also point you to great resources for learning those.
Before we start...
Recommended Prerequisites
The recommended prerequisites for this guide are:
Understanding of essential machine learning concepts
Python programming skills
To move quickly, we'll assume you have this background.
Why Keras?
Keras is our recommended library for deep learning in Python, especially for beginners. Its minimalistic, modular approach makes it a breeze to get deep neural networks up and running. You can read more about it here:
The Keras library for deep learning in Python
WTF is Deep Learning?
Deep learning refers to neural networks with multiple hidden layers that can learn increasingly abstract representations of the input data. This is obviously an oversimplification, but it's a practical definition for us right now.
For example, deep learning has led to major advances in computer vision. We're now able to classify images, find objects in them, and even label them with captions. To do so, deep neural networks with many hidden layers can sequentially learn more complex features from the raw input image:
The first hidden layers might only learn local edge patterns.
Then, each subsequent layer (or filter) learns more complex representations.
Finally, the last layer can classify the image as a cat or kangaroo.
These types of deep neural networks are called Convolutional Neural Networks.
链接: https://elitedatascience.com/keras-tutorial-deep-learning-in-python
原文链接: http://weibo.com/1402400261/EjqMi6r7J?from=page_1005051402400261_profile&wvr=6&mod=weibotime&type=comment#_rnd1480235576335
点击上方“机器学习研究会”可以订阅哦
摘要
转自:爱可可-爱生活
In this step-by-step Keras tutorial, you’ll learn how to build a convolutional neural network in Python!
In fact, we’ll be training a classifier for handwritten digits that boasts over 99% accuracy on the famous MNIST dataset.
Before we begin, we should note that this guide is geared toward beginners who are interested in applied deep learning.
Our goal is to introduce you to one of the most popular and powerful libraries for building neural networks in Python. That means we’ll brush over much of the theory and math, but we’ll also point you to great resources for learning those.
Before we start...
Recommended Prerequisites
The recommended prerequisites for this guide are:
Understanding of essential machine learning concepts
Python programming skills
To move quickly, we'll assume you have this background.
Why Keras?
Keras is our recommended library for deep learning in Python, especially for beginners. Its minimalistic, modular approach makes it a breeze to get deep neural networks up and running. You can read more about it here:
The Keras library for deep learning in Python
WTF is Deep Learning?
Deep learning refers to neural networks with multiple hidden layers that can learn increasingly abstract representations of the input data. This is obviously an oversimplification, but it's a practical definition for us right now.
For example, deep learning has led to major advances in computer vision. We're now able to classify images, find objects in them, and even label them with captions. To do so, deep neural networks with many hidden layers can sequentially learn more complex features from the raw input image:
The first hidden layers might only learn local edge patterns.
Then, each subsequent layer (or filter) learns more complex representations.
Finally, the last layer can classify the image as a cat or kangaroo.
These types of deep neural networks are called Convolutional Neural Networks.
链接: https://elitedatascience.com/keras-tutorial-deep-learning-in-python
原文链接: http://weibo.com/1402400261/EjqMi6r7J?from=page_1005051402400261_profile&wvr=6&mod=weibotime&type=comment#_rnd1480235576335
相关文章推荐
- 深度学习入门之一:Windows10(64)+Anaconda3(Python3.5)+TensorFlow-Gpu1.4+CUDA8.0+cuDNN6安装详解及Pycharm配置指南
- Python入门深度学习完整指南
- 深度学习框架之Keras入门教程
- Python入门深度学习完整指南
- Python中Keras深度学习库的回归教程
- 【TensorFlow深度学习框架教程二】Python一小时入门导学
- python机器学习系列教程——深度学习框架比较TensorFlow、Theano、Caffe、SciKit-learn、Keras
- Python入门深度学习完整指南
- Python入门深度学习完整指南
- 深度学习入门基础 ----- Python快速教程 、深度学习理论基础、Tensorflow基础
- Python学习入门基础教程(learning Python)--3.1Python的if分支语句
- 韩顺平_php从入门到精通_视频教程_第19讲_网站推荐_定位_学习笔记_源代码图解_PPT文档整理
- 免费编程入门教程资源推荐搜集,分享给想开始学习程序开发的同学
- Python学习入门基础教程(learning Python)--3.3.2 Python的关系运算
- Python学习入门基础教程(learning Python)--2.2.1 Python下的变量解析
- Python学习入门基础教程(learning Python)--2.3 Python自定义函数传参
- Python学习入门基础教程(learning Python)--5.2 Python读文件基础
- Python学习入门基础教程(learning Python)--3.3.3 Python逻辑关系表达式
- 免费编程入门教程资源推荐搜集,分享给想开始学习程序开发的同学【转自异次元软件世界】
- 免费编程入门教程资源推荐搜集,分享给想开始学习程序开发的同学