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Papers :Top journals in ML, CV: TPAMI,IJCV, top academic conferences: CVPR,ICML, ICCV,NIPS,ECCV,ACCV, etc.;Cvpapers has done a good job in the field of CV academic papers;ImageNet Annual Image Recognition competition is very representative of the highest level of CV;arxiv.org, many of the latest papers were first published here;Of course, Google Scholar is recommended, this is a mirror site.Learning website :Deeplearning.net: A very good machine
library wholeheartedly. Scikit Learn: This is a machine learning library written in Python, based on NumPy and scipy. If you are a Python or ruby language programmer, this is for you. The library is user-friendly and powerful, with detailed documentation. If you want to try another library, you can choose orange.
-GROWTH algorithm to efficiently discover frequent itemsets Part IV Other tools 13.) Use PCA to simplify data 14.) Simplify data with SVD 15.) Big Data and MapReduce Part V Project Combat (non-textbook content) 16.) Recommendation System Periodic summary Summary of the first phase of 2017-04-08_ Appendix A, getting Started with Python Appendix B Linear Algebra Appendix C Review o
Transferred from: http://www.csdn.net/article/2015-10-16/2825925First of all, let me start with my intentions . Machine learning system now much more red NB this thing I don't have to repeat. But because of the particularity of machine learning system, it is not easy to build a reliable and useful system. Every time I
Machine learning LanguageWhat are the common programming languages for machine learning?Machine Learning (machines learning, ML) is a multidisciplinary interdisciplinary subject involvi
Zero basic learning Python (1) Python environment installation, basic learning python Environment Any advanced language requires a programming environment of its own. This is like writing. It requires paper and pen, writing on a computer, and text processing software, for ex
Python basic learning notes (Python environment) and python learning notes Python first. Summarize the basic knowledge of Python. I. Understanding
actually nearly 20000 citations, really scary. It is not surprising to think carefully, all kinds of research work, as long as the classification, most will use the SVM algorithm or with SVM algorithm comparison, and at this time LIBSVM is often the preferred tool. In fact, not only the academia, LIBSVM in the industrial sector also has a very wide range of applications. This is due to the stability and efficiency of the algorithm implementation, on the other hand because LIBSVM provides a rich
Turn from: 11900000053568571. PrefaceOriginally this title I think is 算法工程师的技能 , but I think if added in the 机器学习 title, the estimated point of people will be a little more, so the title into this, hehe, and is indexed by the search engine when a more popular words, estimated exposure will be more points. But rest assured, the article is not tricky, we are serious.Today, the 机器学习 last two years of the computer field of the hottest topic, this is not a machin
data science to better use it for project development. So if your data science team is it -centric, it might not be your best choice, and we'll talk about simpler alternatives. 1.3 use Caseconsidering the TensorFlow 's complexity, its use cases mainly include solutions for large companies that have experts in the field of machine learning. For example, the UK online supermarket Ocado uses TensorFlow to pri
This blog records "Machine Learning Combat" (machinelearninginaction) learning process, including algorithmic introduction and Python implementation. SVM (Support vector machine) SVM is a classification algorithm, through the analysis of training set data to find the best se
* *.Second, installation Scikit-learnExecute command:Conda Install Scikit-learnSecond, installation KrasExecute command:Conda Install KerasThe required tensorflow is automatically installation during installation of the Keras process.At this point, deep learning, machine learning development environment has been installed, you can commandSpyderOrJupyter Notebook
discriminant models (discriminative model)The generation method is obtained by the data Learning Joint probability distribution P (x, y) and then the conditional probability distribution P (y| X) as the predictive model, the model is generated : P (Y |X )= P(X,Y)p ( X ) This method is called a build method , which represents the generation relationship of output y produced by a given input x. such as: Naive Bayesian and Hidden M
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 learning
Recommended book:Data mining: Practical machine learningData mining: Concepts and Techniques Han Jiawei; Read + reference articles later;Machine learning Combat (python);Machine learning Practical Case Analysis (r language);Neural
Deep learning of wheat-machine learning Algorithm Advanced StepEssay background: In a lot of times, many of the early friends will ask me: I am from other languages transferred to the development of the program, there are some basic information to learn from us, your frame feel too big, I hope to have a gradual tutorial or video to learn just fine. For
Original: Image classification in 5 MethodsAuthor: Shiyu MouTranslation: He Bing Center Image classification, as the name suggests, is an input image, output to the image content classification of the problem. It is the core of computer vision, which is widely used in practice. The traditional method of image classification is feature description and detection, such traditional methods may be effective for some simple image classification, but the traditional classification method is overwhelmed
A collection of 27 machine-Learning small copy There are many aspects of machine learning, and when I started studying it, I found a variety of "small copies" that concisely listed the key points of knowledge for a given topic. In the end, I brought together over 20 machine
reinforcement learning, the input data directly feedback to the model, the model must be immediately adjusted. Common application scenarios include dynamic systems and robot control. Common algorithms include q-learning and time difference learning (temporal difference learning)Ma
Environment construction process is very troublesome ... But finally is ready, first give some of the process of reference to the more important information (find Microsoft's machine learning materials is a personal experience, without any reference):1. If the online various numpy, scipy and so on package installation tutorial trouble, go directly to: Microsoft Machine
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