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tags (space delimited): Wang Cao TensorFlow notes
Note-taker: Wang GrassNote Finishing Time February 24, 2017TensorFlow official English document address: Https://www.tensorflow.org/get_started/mnist/beginnersOfficial documents When this article was compiled last updated: February 15, 2017 1. Case Background
This article is followed by the second tutorial of the official TensorFlow document – Identifying ha
Reproduced in the Daily Digest of deep learning, convlstm principle and its tensorflow realizationThis document references convolutional LSTM network:a machine learning approach forPrecipitation nowcasting
Today introduced a very famous network structure--convlstm, it not only has the LSTM time series modelling ability
[Introduction to machine learning] Li Hongyi Machine Learning notes-9 ("Hello World" of deep learning; exploring deep learning)
PDF
Video
Keras
Example appl
rate, the higher the accuracy.
Mini-batch size. The size of each batch determines the weight update rules. The average value is obtained and the weight is updated only after the entire batch of sample gradients are calculated. The higher the batch, the faster the training speed. The matrix and linear algebra libraries are used for acceleration, and the weight update frequency is low. The smaller the batch, the slower the training speed. Set the machine
learning algorithms which are widely used in image classification in the industry and knn,svm,bp neural networks.
Gain deep learning experience.
Explore Google's machine learning framework TensorFlow.
Below is the detailed implementation details.
First, System design
In thi
Installation use
Official Document Connection: Https://www.tensorflow.org/get_started/get_started_for_beginnersIn accordance with the text of the GitHub connection to download files directly GG, Hung ladder or clone do not move, helpless, had to go to that page to use the example of the py file copy came to the local, need to copy two files:
https://github.com/tensorflow/models/tree/master/samples/core/get_started/iris_data.py
https://github.com/
In the previous article we brought out the network structure of Googlenet InceptionV1, in this article we will detail inception V2/V3/V4 's development process and their network structure and highlights.Googlenet Inception V2Googlenet Inception V2 in "Batch normalization:accelerating deep Network Training by reducing Internal covariate Shift" appears, the largest The highlight is the batch normalization method, which plays the following role:
use larger
Introduction of Style migration
Style Transfer is one of the most interesting applications of deep learning, as shown in this way, we can use this method to "migrate" the style of a picture to another picture:
However, the speed of the original style migration (click to view the paper) is very slow. On the GPU, it takes about 10 minutes to generate a picture, and it may take several hours if you use only the CPU without using the GPU to run the progr
Recently saw a relatively good machine learning course, roughly heard it again. The overall sense of machine learning field is still more difficult, although Li Hongyi teacher said is very good, not enough to absorb up or have a certain difficulty. Even though the process has been told, it is difficult to understand ho
Model optimization is important for both traditional machine learning and deep learning, especially in deep learning, and it is likely that more difficult challenges will need to be addressed during training. At present, the popular and widely used optimization algorithm has a random gradient descent, with the momentum
1. Google Cloud Machine learning Platform Introduction:The three elements of machine learning are data sources, computing resources, and models. Google has a strong support in these three areas: Google not only has a rich variety of data resources, but also has a strong computer group to provide data storage in the dat
First, let's talk about gossip.
If you go to machine learning now, will you go? Is it because you are not interested in this aspect, or because you think this thing is too difficult, you will not learn? If you feel too difficult, very good, believe that after reading this article, you will have the courage to step into the field of machine
article, I describe how to handle the system's own and installed Python versions.Python machine learning related librariesPythonThere are many libraries involved in machine learning, such as,,, and Theano TensorFlow PyTorch scikit-learn so on. Considering that scikit-learn
At present, the application of machine learning business is more in communication and finance. Large data, machine learning these concepts have been popularized in recent years, but many researchers have worked in this field more than 10 years earlier. Now finally ushered in their own tuyere. I will use the professiona
list not to be missed (with electronic version pdf download)Reply to the number "5" Big Data learning materials download, beginner's Guide, data analysis tools, software use tutorialReply to the number "6"ai Artificial Intelligence: 54 Industry Heavyweight report summary (download included)Reply Number "7"tensorflow Introduction, installation tutorial, image rec
networks and overfitting:
The following is a "small" Neural Network (which has few parameters and is easy to be unfitted ):
It has a low computing cost.
The following is a "big" Neural Network (which has many parameters and is easy to overfit ):
It has a high computing cost. For the problem of Neural Network overfitting, it can be solved through the regularization (λ) method.
References:
Machine Learning
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
Original handout of Stanford Machine Learning Course
This resource is the original handout of the Stanford machine learning course, which is AndrewNg said that a total of 20 PDF files cover some important models, algorithms, and concepts in
Original address: http://www.cnblogs.com/cyruszhu/p/5496913.htmlDo not use for commercial use without permission! For related requests, please contact the author: [Email protected]Reproduced please attach the original link, thank you.1 BasicsL Andrew NG's machine learning video.Connection: homepage, material.L 2.2008-year Andrew Ng CS229 machine LearningOf course
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