deep learning with tensorflow course

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Start learning deep learning and recurrent neural networks some starting points for deeper learning and Rnns

Bengio, LeCun, Jordan, Hinton, Schmidhuber, Ng, de Freitas and OpenAI had done Reddit AMA's. These is nice places-to-start to get a zeitgeist of the field.Hinton and Ng lectures at Coursera, UFLDL, cs224d and cs231n at Stanford, the deep learning course at udacity, and the sum Mer School at IPAM has excellent tutorials, video lectures and programming exercises th

Evaluation and comparison of deep learning framework

Turn from deep learning public numberThis article is from: InfoQHttp://www.infoq.com/cn/news/2016/01/evaluation-comparison-deep-learnArtificial intelligence is undoubtedly the forefront of the computer world, and deep learning is undoubtedly the focus of artificial intellige

Evaluation and comparison of deep learning framework

Article source:http://www.infoq.com/cn/news/2016/01/evaluation-comparison-deep-learn?utm_campaign=infoq_content Evaluation and comparison of deep learning frameworkArtificial intelligence is undoubtedly the forefront of the computer world, and deep learning is undoubtedly th

Deep Learning (depth learning) Learning Notes finishing series (vi)

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

Special methods and multi-paradigm for Python deep learning, and python deep learning paradigm

Special methods and multi-paradigm for Python deep learning, and python deep learning paradigm Python is an object. But at the same time, Python is also a multi-paradigm language. You can not only write programs in an object-oriented way, you can also use process-oriented methods to compile programs with the same funct

Deep Learning (Depth study) (ii) The basic idea of the profound learning

The basic thought of deep learningSuppose we have a system s, which has n layers (S1,... SN), its input is I, the output is O, the image is expressed as: I =>S1=>S2=>.....=>SN = o, if the output o equals input I, that is, input I after this system changes without any information loss (hehe, Daniel said, it is impossible.) In the information theory, there is a "message-by-layer-loss" statement (processing inequalities), the processing of a information

Machine Learning Professional Advanced Course _ Machine learning

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 professional experience of millions of machine-learning

Deep Learning (depth learning) Learning notes finishing Series (iv)

classifier.In the study, it can be found that if the original features are added to the characteristics of the automatic learning can greatly improve the accuracy, even in the classification of the best classification algorithm than the current effect is better!There are some variants of autoencoder, here is a brief introduction to the next two:Sparse Autoencoder Sparse Automatic encoder:Of course, we can

Google Self-study courses: deep Learning and Tensorflow_ integrated application

Original English: Teach Yourself Deep Learning with TensorFlow Author: Vincent Vanhoucke,google chief Scientist. Translation: Guokai Han. In recent years, deep learning has become one of the hottest topics in the field of machine learnin

Deep Learning: 16 (deep networks)

converge to a better local optimal solution. If it is a parameter value of the random initialization model, it is generally difficult to converge to a local good value in a multi-layer neural network, because the system functions of the multi-layer neural network are non-convex. So when should I use the fine-tuning Technology to adjust the result of unsupervised learning? Only a large number of labeled samples can be used. Fine-tuning technology is n

The application of deep learning in the ranking of recommended platform for American group Review--study notes

-depth learning model Framework:In the offline phase, we use the theano, tensorflow-based Keras as the model ENGINE. At the time of training, we separately cleaned and weighted the sample Data. In terms of features, we use the Min-max method for normalization of continuous features. In terms of cross-features, we combine business requirements to refine multiple cross-features that are more significant in bu

Deep Learning notes ------ windows system for Linux-Ubuntu14.04 dual system installation notes (a), deep linux dual system installation notes

Deep Learning notes ------ windows system for Linux-Ubuntu14.04 dual system installation notes (a), deep linux dual system installation notes Currently, deep learning is widely used in target detection and Classification Research, and most Neural Network frameworks (such as

Application of deep learning in data mining

250 CPU servers.NVIDIA Tesla? P100 Accelerator.First video card with Pascal architectureOwns 18 billion transistorsUsing NVIDIA Nvlink?Manufacturing process using 16nm FinFETThe Tesla P100 is not only the most powerful GPU accelerator today,It's also the most technologically advanced GPU chip.Distributed deep learning system for DatainsightBased on the TensorFlow

Deep Learning Application Series (iii) | Build your own image recognition app using Tflite Android

Deep learning to practice, an indispensable path is to the intelligent terminal, embedded equipment and other directions. But the terminal device does not have the powerful performance of GPU server, how to make the end device application deep learning? Fortunately, Google has launched the tfmobile, last year furthe

How to correctly understand the concept of deep learning (learning)

in these applications, has achieved very good results (even the state of art), but because of this time is unacceptable, limiting its application in the promotion of practical. By now, the level of computer hardware has not been the same as before, so a model of neural networks into the people's eyes. " from Google brain This project we can see that the neural network model for the computational requirements is extremely large, in order to ensure the real-time nature of the algorithm,

Setting up a deep learning machine from Scratch (software)

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

The application of deep learning in the ranking of recommended platform for American group reviews

found that the simple DNN model was not significantly improved for CTR. and the individual DNN model itself has some bottlenecks, for example, when the user itself is a non-active user, because the interaction between itself and item is relatively small, resulting in a very sparse eigenvector, and deep learning model in dealing with this situation may be excessive generalization, Causes the recommendation

"Reprint" How to self-study deep learning technology, great God Yann LeCun Pro-Grant Advice

legal reasons, but PPT is still there. In the spring of 2017, I will be teaching this course at New York University again. Website: http://cilvr.nyu.edu/doku.php?id=deeplearning2015%3Aschedule) In 2015, a "deep learning Summer Course" was held in Montreal, Canada, which was targeted at: graduate students, industry

Deep learning "engine" contention: GPU acceleration or a proprietary neural network chip?

envy its "local tyrants" behavior, If there is a nvlink, there is obviously another good way to do it.Of course, wanting to use nvlink also means new investments, and Nvidia's existing product line supports deep learning, which users can choose to do as appropriate. For more in-depth knowledge of hardware selection, you can refer to the blog post written by Kagg

opencv+ Deep Learning pre-training model for simple image recognition | Tutorial

Reprint: Https://mp.weixin.qq.com/s/J6eo4MRQY7jLo7P-b3nvJg Li Lin compiled from PyimagesearchAuthor Adrian rosebrockQuantum bit Report | Public number Qbitai OpenCV is a 2000 release of the open-source computer vision Library, with object recognition, image segmentation, face recognition, motion recognition and other functions, can be run on Linux, Windows, Android, Mac OS and other operating systems, with lightweight, efficient known, and provides multiple language interfaces. OPENCV's latest

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