theano deep learning

Deep reinforcement learning with Double q-learningGoogle DeepMind　　AbstractThe mainstream q-learning algorithm is too high to estimate the action value under certain conditions. In fact, it was not known whether such overestimation was common, detrimental to performance, and whether it could be organized from the main body. This article answers the above question

This article for the original article reproduced must indicate the source of this article and attached this article address hyperlink and blog address: http://blog.csdn.net/qq_20259459 and author mailbox (jinweizhi93@gmai.com). (If you like this article, you are welcome to pay attention to my blog or to do a bit of praise, there is a need to mail contact me) As for this article, I really wanted to write about it last week, but I have always felt that it has to be considered before writing. Firs

Deep learning GroupsSome Labs and groups that is actively working on deep learning:University of Toronto-machine Learning Group (Geoffrey Hinton, Rich Zemel, Ruslan Salakhutdinov, Brendan Frey, Radford N EalUniversitéde montréal– MILA Lab (Yoshua Bengio, Pascal Vincent, Aaron Courville, Roland Memisevic)New York univer

These two days have taken a lot of effort to carry a deep learning Python architecture, but Theano has limitations on Python and nunpy versions, so you can only use newer versions of Python and nunpy to make sure it's not obsolete. But the most recent version of Python and the latest edition of NumPy is a bit imperfect, a lot of installation steps to be completed

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

industry for image classification with KNN,SVM,BP neural networks. Gain deep learning experience. Explore Google's machine learning framework TensorFlow. Below is the detailed implementation details. System Design In this project, 5 algorithms for experiments are KNN, SVM, BP Neural Network, CNN and Migration Learning

Happy New Year! This is a collection of key points of AI and deep learning in 2017, and ai in 2017RuO puxia Yi compiled from WILDMLProduced by QbitAI | public account QbitAI 2017 has officially left us. In the past year, there have been many records worth sorting out. The author of the blog WILDML, Denny Britz, who once worked on Google Brain for a year, combed and summarized the AI and

install-y Python-pip Recommendation:The installation process is best a command one command implementation, there was a mistake to facilitate timely discovery.Installation process has failed to install the situation, do not worry, usually because of network reasons, re-execute the command, generally try a few times will be good ~3. cuda8.0DownloadOfficial website Download: https://developer.nvidia.com/cuda-downloadsDirect download: cuda-repo-ubuntu1604-8-0-local_8.0.44-1_amd64.debInstallatio

Course Address: Https://class.coursera.org/ntumltwo-002/lectureImportant! Important! Important!1. Shallow-layer neural networks and deep learning2. The significance of deep learning, reduce the burden of each layer of network, simplifying complex features. Very effective for complex raw feature learning tasks, such as