machine learning with tensorflow book

Reprinted please indicate Source Address: http://www.cnblogs.com/xbinworld/archive/2013/04/21/3034300.html Pattern Recognition and machine learning (PRML) book learning, Chapter 1.1, introduces polynomial curve fitting) The doctor is almost finished. He will graduate next year and start preparing for graduation

Original writing. For more information, see http://blog.csdn.net/xbinworld,bincolumns. Pattern Recognition and machine learning (PRML) book learning, Chapter 1.1, introduces polynomial curve fitting) The doctor is almost finished. He will graduate next year and start preparing for graduation this year. He feels that he

Hyperopt Numpic 2012-paper-diginorm Ipython-notebooks Demo-weights Sarah Palin lda-Sarah Palin's email about topic modeling. Diffusion segmentation-a set of image segmentation algorithms based on the diffusion method. Scipy tutorials-scipy tutorial. It is out of date. Please refer to scipy-lecture-notes Crab-Python recommendation engine library. Bayesian inference tool in bayespy-Python. Scikit-learn tutorials-scikit-learn learning notes S

. The teacher is speaking in layman's terms, not worrying too much about math. And the work is also very suitable for beginners, are well-designed program framework, there is a job guide, according to the work guide to fill in the completed part of the line. This course is over, you can basically start a simple application of a variety of machine learning technology.2. Find a project or find a slightly more

Selected top 32 machine learning open source project, organized from Mybridge AI: 1. Fasttext: Quick text representation and text classification library (11786 stars on GitHub, contributor Facebook) SOURCE Link: Https://github.com/facebookresearch/MUSE 2. Deep-photo-styletransfer: "Deep photo Style Transfer" The source and data of this paper. (GitHub 9747 stars, papers from Cornell University's Fujun Luan)

corresponds to different C, while the longitudinal axes represent different gamma.The above diagram shows the use of cross-validation method we choose the least error of the model parameter, we can only select a few different C and γ, compare which parameter combination of the form is better.Relationship between SVM and support vectors with a cross-validation errorOne of the interesting relationships in SVM is that the error of leaving a cross-validation is less than or equal to the scale of th

. Important modules of machine learning The most important modules of machine learning are NumPy, Pandas, Matplotlib, and IPython. One book covers some of the modules: Data Pipeline Analysis Platform with Open Source pipeline Tools. Then from 1. the free

for special purposes; some cooperation vendors have developed several interchangeable engines (such as Allaire JRun and Apache JServ ). Theoretically, Active Server Pagesb allows one of the vast majority of scripting languages and several compatible ActiveX scripting engines (however, in practice, except for the combination of NT, IIS, VBScript, and JScirpt, there are many other combinations.) due to PHP4's scriptingz engine (Zend) at present, it is theoretically separated from the PHP programm

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

simple machine learning tasks. However, the choice of what library is completely subjective, and many people in the industry have a lot of controversy.Some of the useful Python libraries include: Scikit-learn: An elegant library of machine learning algorithms that can be used for data mining and data analysis

say. However, two books are recommended for those who have just contacted NLTK or need to know more about NLTK: One is the official "Natural Language processing with Python" to introduce the function usage in NLTK, with some Python knowledge, At the same time the domestic Chen Tao classmate Friendship translated a Chinese version, here you can see: recommended "natural language processing with Python" Chinese translation-nltk supporting book; another

can be accessed online. You can use the following command to export a "naked warehouse" and then use the SCP command to copy them to your server:$ git clone --bare /home/user/myrepo/.git /tmp/myrepo.git$ scp -r /tmp/myrepo.git myserver.com:/opt/git/myrepo.gitIf other people also have an SSH account on the myserver.com server, TA can clone the (clone) code from this server:clone myserver.com:/opt/git/myrepo.gitThe above command will prompt you to enter the SSH password or use the public key.Viii

, linear algebra library to accelerate the calculation, the smaller batch, the acceleration effect may be less obvious. Of course, batch is not the bigger the better, too big, the weight of the update will be less frequent, resulting in the optimization process is too long. So mini-batch size, not static, according to your data set size, your device computing ability to choose. The the-Go is therefore-use some acceptable (but not necessarily-optimal) values for the other hyper-parameter

of the update will be less frequent, resulting in the optimization process is too long. So mini-batch size, not static, according to your data set size, your device computing ability to choose. The the-Go is therefore-use some acceptable (but not necessarily-optimal) values for the other hyper-parameters, and Then trial a number of different mini-batch sizes, scalingηas above. Plot the validation accuracy versus time (as in, real elapsed time, not epoch!), and choose whichever mini-bat

computer, and each instruction represents one or more operations.Give a simple example, and you can use it in your life. Now make a small game, a on the paper randomly wrote a 1 to 100 integer, b to guess, guess the game is over, guess the wrong word a will tell B guess small or big. So what will b do, the first time you must guess 50, guess the middle number. Why is it? Because of this worst case scenario (log2100">Log2log2100) Six or seven times can be guessed.This is a binary search, which m

After 2 months of knowledge of machine learning. I've found that machine learning has a variety of directions. Page sort. Speech recognition, image recognition, recommender system, etc. Algorithms are also varied. After seeing the other books, I found that except for the K-mean clustering. Bayesian, neural network, onl

.ManagementGigabytes, A good book for information retrieval. 7.Information Theory: inference and learningAlgorithmsFor more information, see. Related mathematical BASICS (reference books are not suitable for general reading ): 1. Linear Algebra: This reference book will not be listed. 2. Matrix mathematics:Matrix Analysis, RogerHorn. Classic in the field of matrix analysis. 3.Probability Theory and sta

, transformation, measurement, division and so on in Lie groups are important for the study of algebraic methods in learning.9 , graph theory (graph theory)Figure, due to its strong ability to express various relationships and elegant theory, efficient algorithm, more and more popular in the field of learning. Classical graph theory, one of the most important applications in

~ ~): Machine learning, data mining (the second half of the main entry): "Introduction to Data Mining" read a few chapters, feel good. Read the review again. "Machine learning" Stanford Open Class is the main. "Linear Algebra", seventh edition, American Steven J.leon There are examples of applications, looking at

both.Jieba-Chinese word breaker toolSNOWNLP-Chinese Text Processing libraryLoso-Another Chinese word-breaking libraryGenius-Chinese word-breaking database based on conditional random domainNut-Natural Language Understanding ToolkitGeneral Machine LearningBayesian Methods for Hackerse-Book for-python language probabilistic programmingMLlib in Apache SparkDistributed mac