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Original address machine learning in the Cloud, with TensorFlowWednesday, MarchPosted by Slaven Bilac, software Engineer, Google analyticsmachine learning in the cloud with TensorFlowat Google, researchers collaborate closely and product teams, applying the latest advances in machine
TensorFlow integrates and implements a variety of machine learning-based algorithms that can be called directly.Supervised learning1) Decision Trees (decision tree)Decision tree is a tree structure, providing people with decision-making basis, decision tree can be used to answer yes and no problem, it through the tree structure of the various situations are repre
. summaries.py includes an auxiliary function to generate the day to record, summaries_test.py is one of its tests, using the example below:
Import TensorFlow as TFSlim = Tf.contrib.slim
Slim.summaries.add_histogram_summaries (Slim.variables.get_model_variables ())Slim.summaries.add_scalar_summary (Total_loss, ' total loss ')Slim.summaries.add_scalar_summary (learning_rate, ' learning rate ')Slim.summaries.
Deep learning has a profound effect on computer science. It makes it possible for cutting-edge technology to research and develop products that are used by tens of millions of of people everyday.The study announced the launch of the second-generation machine learning System (TENSORFLOW), which has been strengthened for
Last year in Beijing participated in a big data conference organized by O ' Reilly and Cloudera, Strata , and was fortunate to have the O ' Reilly published hands-on machine learning with Scikit-learn and TensorFlow English book, in general, this is a good technical book, a
TensorFlow v0.11.0 RC1 Released, TensorFlow is Google's second-generation machine learning system, according to Google, in some benchmarks, tensorflow performance than the first generation of distbelief faster than twice times.
Extended support for
Pattern Recognition field Application machine learning scene is very many, handwriting recognition is one of the most simple digital recognition is a multi-class classification problem, we take this multi-class classification problem to introduce Google's latest open source TensorFlow framework, The content behind the deep le
Support original, more content Welcome to the author blog:http://www.china10s.com/blog/?p=490
Machine learning This method of calculation has been known to the world in the last century, but it has not been developed because of the computer-limited computing power and network speed. With the Moore effect, the current computer performance has soared, even in the hands of the iphone, than the United States on
Amazon open machine learning system source code: Challenges Google TensorFlowAmazon took a bigger step in the open-source technology field and announced the opening of the company's machine learning software DSSTNE source code. This latest project will compete with Google's TensorF
First, Introduction
In many machine learning and depth learning applications, we find that the most used optimizer is Adam, why?
The following is the optimizer in TensorFlow:
See also for details: Https://www.tensorflow.org/api_guides/python/train
In the Keras also have Sgd,rmsprop,adagrad,adadelta,adam, details: https
Objective
Because of the problem of image Learning machine learning, choose TensorFlow, but seems to go directly from the example of imagenet, but found how to find the end (Python will not, machine learning also do not understand
decision trees (decision tree) 4
Cited examplesThe existing training set is as follows, please train a decision tree model to predict the future watermelon's merits and demerits.Back to Catalog
What are decision trees (decision tree) 5
Cited examplesThe existing training set is as follows, please train a decision tree model to predict the future watermelon's merits and demerits.Back to Catalog
What are decision trees (decision tree) 6
Machine learning and Data Mining recommendation book listWith these books, no longer worry about the class no sister paper should do. Take your time, learn, and uncover the mystery of machine learning and data mining. machine
(written in front) said yesterday to write a machine learning book, then write one today. This book is mainly used for beginners, very basic, suitable for sophomore, junior to see the children, of course, if you are a senior or a senior senior not seen machine
Https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.mdMachine-learning/data Mining
An Introduction to statistical learning-book + R Code
Elements of statistical Learning-
and is easily downloaded and modified by the reader.The following books will not be introduced, share the graphic coverHere is still to recommend my own built Python development Learning Group: 725479218, the group is the development of Python, if you are learning Python, small series welcome you to join, everyone is the software Development Party, not regularly share dry goods (only Python software develo
Machine learning is often in dealing with maths, so reading a book is certainly essential. Here are some of the books that I have read and find helpful, and I hope it will be helpful to everyone. (Please ignore the bad typography, this typesetting function is too difficult to use.) )Topology:Munkres J R. "Topology"Topology only read this one, can only be said to
Here is a list of books which I had read and feel it was worth recommending to friends who was interested in computer Scie nCE.Machine Learningpattern recognition and machine learningChristopher M. BishopA new treatment of classic machine learning topics, such as classification, regression, and time series analysis from a Ba Yesian perspective. It is a must read
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