keras deep learning tutorial

Deep learning is a prominent topic in the AI field. it has been around for a long time. It has received much attention because it has made breakthroughs beyond human capabilities in computer vision (ComputerVision) and AlphaGO. Since the last investigation, attention to deep learning has increased significantly.

Chinese books. But "machine learning", "statistical learning method" is still worth a look. Foreign language Recommendation "Pattern Recognition and machine learning" and "Machine learning:a Probabilistic Perspective", the latter containing the chapters of the Deep Neural network。 3.

Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a

Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a

Python1. Theano is a Python class library that uses array vectors to define and calculate mathematical expressions. It makes it easy to write deep learning algorithms in a python environment. On top of it, many classes of libraries have been built.1.Keras is a compact, highly modular neural network library that is designed to reference torch, written in Python, t

Setting up a deep learning machine from Scratch (software)A detailed guide-to-setting up your machine for deep learning. Includes instructions to the install drivers, tools and various deep learning frameworks. This is tested on a

Mark, let's study for a moment.Original address: http://www.csdn.net/article/2015-09-15/2825714Python1. Theano is a Python class library that uses array vectors to define and calculate mathematical expressions. It makes it easy to write deep learning algorithms in a python environment. On top of it, many classes of libraries have been built.1.Keras is a compact,

###### #编程环境: Anaconda3 (64-bit)->spyder (python3.5)fromKeras.modelsImportSequential #引入keras库 fromKeras.layers.coreImportDense, Activationmodel= Sequential ()#Building a modelModel.add (Dense (12,input_dim=2))#Input Layer 2 node, hide layer 12 nodes (The number of nodes can be set by itself)Model.add (Activation ('Relu'))#Use the Relu function as an activation function to provide significant accuracy Model.add (Dense (1,input_dim=12))#dense hidden la

ObjectiveFor deep learning, novice I recommend to see UFLDL first, do not do assignment words, one or two nights can be read. After all, convolution, pooling what is not a particularly mysterious thing. The course is concise, sharply, and points out the most basic and important points.cs231n This is a complete course, the content is a bit more, although the course is computer vision, but 80% is the content

kinds of people, and then now this thing began to become hot, do not know will be like Google glasses. As for the development of DRL, let's look at how those individuals shout!Second,Scientific Review First to the Chinese, this analysis DRL more objective, the recommended index of 3 stars http://www.infoq.com/cn/articles/atari-reinforcement-learning. But in fact, it is only said a fur, really want to see the content of the words or to

Deep Q Network 4.1 DQN Algorithm Update 4.2 DQN Neural Network 4.3 DQN thinking decision 4.4 OpenAI Gym Environment Library Notesdeep q-learning algorithmThis gives us the final deep q-learning algorithm with experience Replay:There is many more tricks this DeepMind used to actually make it wo

About TensorFlow a very good article, reprinted from the "TensorFlow deep learning, an article is enough" click to open the link Google is not only the leader in big data and cloud computing, but also has a good practice and accumulation in machine learning and deep learning