ruby machine learning

A probe into machine learning1. What is machine learningLearning refers to the skill that a person refines in the course of observing things, rather than learning, machine learning refers to the ability of a computer to gain some experience (i.e. a mathematical model) in a p

[Machine learning algorithm-python implementation] matrix denoising and normalization, python Machine Learning1. The background project is required. We plan to use python to implement matrix denoising and normalization. The numpy mathematical library does not find ideal functions. Therefore, I wrote a de-noise and normalization algorithm in the standard library,

Pick up a Redis Ruby client learning (ii)For the five data types of Redis: string, hash (Map), list, collection (sets) , and ordered collection (sorted sets), the previous article describes the hashes and lists.One, assemble Mset Add one or more elements to the collection (set) " Redis " ='my_set'value1' SCard. Returns the cardinality of the key stored by the collection (the number o

Machine learning practices in python3.x and python machine learning practices Machine Learning Practice this book is written in the python2.x environment, while many functions and 2 in python3.x. the names or usage methods in x ar

findF1scoreThe algorithm with the largest value. 5. Data for Machine Learning ( Machine Learning data ) In machine learning, many methods can be used to predict the problem. Generally, when the data size increases, the accura

Core ML machine learning, coreml Machine Learning At the WWDC 2017 Developer Conference, Apple announced a series of new machine learning APIs for developers, including visual APIs for facial recognition and natural language proce

Microsoft Azure cloud service introduces the machine learning module. Users only need to upload data and use some algorithm interfaces and R or other language interfaces provided by the machine learning module, you can use Microsoft Azure's powerful cloud computing capabilities to implement your

Directly run the Code: Module action def jump @ distance = rand (4) + 2 puts "I jumped forward # {@ DISTANCE} feet! "Endendclass rabbit include action attr_reader: Name def initialize (name) @ name = Name endclass cricket include action attr_reader: Name def initialize (name) @ name = Name endendpeter = rabbit. new ("Peter") Jiminy = cricket. new ("Jiminy") Peter. jumpjiminy. jump ---------------------------------------------------------------------- output: I jumped forward 3 feet! I jumped for

The essential difference between classification and clustering in machine learning There are two kinds of big problems in machine learning, one is classification, the other is clustering.In our life, we often do not have too much to distinguish between these two concepts, think clustering is classification, classificat

libraryBayespyBayesian inference tool in-pythonScikit-learn Tutorials-scikit-learn Study Notes SeriesSentiment-analyzer-Twitter Sentiment analyzerGroup-lasso-coordinate descent algorithm experiment, applied to (sparse) Group Lasso modelMne-python-notebooks-Ipython notes for EEG/MEG data processing using Mne-pythonPandas Cookbook-a method book using the Python Pandas libraryClimin-Machine learning Optimizat

1. Decision Tree　　applicable conditions: The data of different class boundary is non-linear, and by continuously dividing the feature space into a matrix to simulate. There is a certain correlation between features. The number of feature values should be similar, because the information gain is biased towards more numerical characteristics.　　Advantages: 1. Intuitive decision-making rules; 2. Nonlinear characteristics can be handled; 3. The interaction between variables is considered.　　Disadvanta

are as follows:Lambda Train error Validation error 0.000000 0.173616 22.066602 0.001000 0.156653 18.597638 0.003000 0.190298 19.981503 0.010000 0.221975 16.969087 0.030000 0.281852 12.829003 0.100000 0.459318 7.587013 0.300000 0.921760 1.000000 2.076188 4.260625 3.000000 4.901351 3.822907 10.000000 16.092213 9.945508 Training errors, cross-validation errors, and relationships between lambda graphs are represented as follows:When th

Ruby learning Note 2 helps generate code for Vim to add code headers, rubyvim The script language is too strong. My goal is to add my default code header function to Vim. /******************************************************************************* COPYRIGHT NOTICE* Copyright (c) 2014 All rights reserved* ----Stay Hungry Stay Foolish----** @author : Shen* @name :* @file : G:\My Source Code\Def

' s Amethod def Amethod (A, B, c) superend5. Constants and Nested classes (constants nested Class)Class= ten class Y def xyz "Goodbye " ) end end def self.abc puts (" Hello") endendConstant: A variable that begins with an uppercase letter.If you want to access constants or internal classes, you need:puts (x::a) x::abc # You can also use:: To invoke Methods X.ABC # Of course this can also be = x::y.newob.xyz6. Partial classes (partial class)In

Include a table but or a variable in a ruby string. To replace an expression or variable with a different value1 Printf-style methods like Java or PythonTemplate ='Oceania have always been at the war with%s.'Template%'Eurasia' #= = "Oceania have always been at the war with Eurasia."Template%'Eastasia' #= = "Oceania have always been at the war with Eastasia."'To 2 decimal places:%.2f'%Math::P i# = "to 2 decimal places:3.14"'zero-padded:%.5d' %Math::P i

String is the most commonly used class in almost all object-oriented programming languages, and is no exception in Ruby, which is documented in several common methods of string in Ruby.Concat: Connect 2 strings, sample:Output: Hello world!Capitalize: Even the first letter uppercase, the other letter lowercase, example:Output: Hello world!Downcase: Convert to lowercase, sample:Output: Hello world!UpCase: Capitalization, example:Output: HELLO world!Swap

Recommended BooksHere is a list of books which I had read and feel it was worth recommending to friends who was interested in computer Scie nCE.Machine Learningpattern recognition and machine learningChristopher M. BishopA new treatment of classic machine learning topics, such as classification, regression, and time series analysis from a Ba Yesian perspective. I

1. What is machine learningMachine learning is the conversion of unordered data into useful information.The main task of machine learning is to classify and another task is to return.Supervised learning: It is called supervised learning