deep learning with keras

above. Move right to erase the non-0-bit to the right of the decimal points of the result. These non-0 bits are actually positive, but because they are erased, the result subtracts the values of the non-0 bits represented by the original negative result, and the final result is rounded down rather than rounded to 0. Floating point number: Standard for representing floating-point numbers and their operations: IEEE Standard 754. Floating-point numbers are normalized, non-nor

In view of my knowledge of machine learning and statistics, insufficient, temporarily do not translate. I just write down the original English, there may be mistakes, quite fun. Also saw a piece of Chinese article, found in the video recorded in the Deep learning development of the time point. First, record the difference between

In recent years, machine learning, represented by deep learning, has become more and more in the field of health care. According to the type of data processed can be divided into numerical, textual and image data; This paper focuses on text data. Clinical Diagnostic Decisions: (Miotto r,et al;2016) [1] A new unsupervised depth feature

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

First, prefaceAs deep learning continues to evolve in areas such as image, language, and ad-click Estimation, many teams are exploring the practice and application of deep learning techniques at the business level. And in the Advertisement Ctr forecast aspect, the new model also emerges endlessly: Wide and

Transferred from: http://baojie.org/blog/2013/01/27/deep-learning-tutorials/A few good deep learning tutorials, with basic videos and speeches. Two articles and a comic book are attached. There are some additions later.Jeff Dean @ StanfordHttp://i.stanford.edu/infoseminar/dean.pdfAn introductory introduction to what DL

training, scale presents a problem for deep learning. The need to fully interconnect neurons, particularly in the upper layers, requires immense compute power. The first layer for an image-processing application could need to analyze a million pixels. The number of connections in the multiple layers of a deep network would be the orders of magnitude greater. "Th

Deep learning has been fire for a long time, some people have been here for many years, and some people have just begun, such as myself. How to get into this field quickly in a short period of time to master deep learning the latest technology is a question worth thinking about. In the present situation, it is the best

In the previous sections, we have covered what is target detection and how to detect targets, as well as the concepts of sliding windows, bounding box, and IOU, non-maxima suppression.Here will summarize the current target detection research results, and several classical target detection algorithms to summarize, this article is based on deep learning target detection, in the following sections, will be spe

The article was transferred from the deep learning public numberDeep learning is a new field in machine learning that is motivated by the establishment and simulation of a neural network for analytical learning of the human brain, which mimics the mechanisms of the human bra

-ser Ies-based Anomaly DetectIon algorithms AI Class Introduction search algorithms A-star heuristic search Constraint satisfaction algorithms with AP Plications in computer Vision and scheduling Robot Motion planning hillclimbing, simulated annealing and genetic algorithm S 2. Stanford University opened a course on "deep learning and natural language processing" in March: Cs224d:deep

1. Current situation:Deep learning is now very hot, and all kinds of meetings have to be stained with this point. Baidu Brain, Google's brain plan to engage in this. In some areas have achieved very good results, chip recognition, speech recognition, in the security field and even the identification of encryption protocols. The accuracy of the lab in the field of speech is over 90%.2. The essence of deep le

Original link: https://www.paypal-engineering.com/tag/data-science/absrtact: with the explosive growth of data and thousands of machine clusters, we need to adapt the algorithm to run in such a distributed environment. Running machine learning algorithms in a common distributed computing environment has a number of challenges. This article explores how to implement and deploy deep

The history of CNNIn a review of the 2006 Hinton their science Paper, it was mentioned that the 2006, although the concept of deep learning was proposed, but the academic community is still not satisfied. At that time, there was a story of Hinton students on the stage when the paper, machine learning under the Taiwan Daniel Disdain, questioned your things have a

21. Application of Depth neural network in visual significance (visual Attention with deep neural Networks) (English, conference papers, 2015, IEEE Search)This article focuses on the application of CNN in the field of significance detection.　　22. Progress in deep learning Research (Chinese, Journal, 2015, net)A summary article on

CNN began in the 90 's lenet, the early 21st century silent 10 years, until 12 Alexnet began again the second spring, from the ZF net to Vgg,googlenet to ResNet and the recent densenet, the network is more and more deep, architecture more and more complex, The method of vanishing gradient disappears in reverse propagation is also becoming more and more ingenious.　　　　 LeNet AlexNet Zf Vgg Googlenet ResNet Densenet

since the beginning of the 2016, the use of neural networks and deep learning Alphago to win the Master of Human go, deep learning is also considered to be the closest machine learning approach to AI. from the current development trend of the global AI, the

Deep learning est mort. Vive differentiable programming! This English-French mixed words, translated into Chinese, is "deep learning is dead, can be differential programming long live." It is one of the big three in deep learning:

/ * copyright notice: Can be reproduced arbitrarily, please be sure to indicate the original source of the article and author information . */Author: Zhang JunlinTimestamp:2014-10-3This paper summarizes the application methods and techniques of deep learning in natural language processing in the last two years, and the related PPT content, please refer to this link, and the main outline is listed here

This section begins the Basic theory system learning phase of machine learning and deep learning, and the blog content is the notes that are collated during the learning process.1. Machine learningConcept: Multi-disciplinary interdisciplinary, involving probability theory, s