deep learning tutorial tensorflow

two ways to configure deep learning environments: 1. Install directly on the development machine (note that other programs that rely on Python to run may not work): sudo pip installtensorflow-1.2.0rc2-cp27-cp27mu-manylinux1_x86_64.whl-ihttp://mirrors.aliyun.com/pypi/simple/-- Trusted-host mirrors.aliyun.com The cp27 of the WHL file means that using python2.7 cp27m is the ABI attribute 2. Virtualization in

7 mins version:dqn for Flappy Bird Overview This project follows the description of the "Deep Q Learning algorithm described" Playing Atari with deep reinforcement L Earning [2] and shows that this learning algorithm can is further generalized to the notorious Flappy Bird. installation Dependencies: Python 2.7 or 3

1.1 machine learning basics-python deep machine learning, 1.1-python Refer to instructor Peng Liang's video tutorial: reprinted, please indicate the source and original instructor Peng Liang Video tutorial: http://pan.baidu.com/s/1kVNe5EJ 1. course Introduction 2. Machine

Toronto this year's deep learning courseware material):http://www.cs.toronto.edu/~rgrosse/csc321/calendar.htmlUFLDL Tutorial-ufldl (Stanford's deeplearning Introductory tutorial): Http://deeplearning.stanford.edu/wiki/index.php/UFLDL_TutorialDeep Learning Concise

similar to the dimensionality reduction) method. Maximum pooling divides the input image into overlapping image matrix blocks, and each sub-region outputs its maximum value. The two reasons why the maximum pooling method is very effective in the visual processing problem are:(1) Reduce the computational complexity of the upper level by reducing the non-maximum value.(2) The result of pooling supports translation invariance. In the convolution layer, each pixel point has 8 orientations that can

many problems do not have an intuitive physical meaning), so they can achieve better results in large-scale training data.. In addition, from the perspective of Pattern Recognition features and classifiers, the deep learning framework combines feature and classifier into a framework and uses data to learn feature, this reduces the workload of manually designing feature (which is the most effort by engineer

the beginning of the 8 million-dollar venture, it deserves attention. Back to the course, cs224d can be translated as "deep learning for Natural language processing (Deepin learning for Natural Language processing)", which is an on-campus course for Stanford students, However, the relevant material of the course is put on the net, including course video, coursew

convolutional Neural Network Primer (1) Original address : http://blog.csdn.net/hjimce/article/details/47323463 Author : HJIMCE convolutional Neural Network algorithm is an n-year-old algorithm, only in recent years because of deep learning related algorithms for the training of multi-layered networks to provide a new method, and now the computing power of the computer is not the same level of computing, an

fully test the compatibility of good win8, if there are similar small partners in the first two issues after the solution is still not normal use of Python, direct change system. (b) Sure enough, after the change of Win7, everything goes well, you can normally use Python's general functions (now python3.6). Of course, whether it is machine learning or deep learning