QA Official

C# Method of Splitting Arrays 2019-04-06
1. Program Functions this program is mainly to split an array into several blocks. the specific algorithm is as follows: if the array has several elements, use this method to split into several new arrays, use List<T > class to store the newly split array, and ensure that each array has at least one element.This algorithm is similar to pigeonhole principle. For example, if the original array has 10 elements and is split into 5 small arrays, then according to the above algorithm, 5 small arrays will be generated, each array has 2 elements.

IT Interview Experience: How to Write Project Experience on Resume?3 moves to teach you to pack! 2019-04-06
Generally speaking, the project experience and the work experience in the resume complement each other. Compared with the work experience, the project experience focuses more on showing the skill level of the job seeker in a certain professional field.Therefore, both technical posts and scientific research posts attach great importance to project experience in recruitment.How to write project experiences that impress HR?Let me show you three moves. Number 1: Distinguish between work experience and project experience

My Jumble of Computer Vision 2019-04-06
I am going to maintain this page to record a few things about computer vision that I have read, am doing, or will have a look at. Previously I’d like to write short notes of the papers that I have read. It is a good way to remember and understand the ideas of the authors. But gradually I found that I forget much portion of what I had learnt because in addition to paper I also derive knowledges from others’ blogs, online courses and reports, not recording them at all.

R Language -reshape2 2019-04-06
R Language Learning Notes -reshape2 reshape2 is a powerful R package for data processing operations. Main function, Mel, * cast. two functions melt ###S3 method for class 'data.frame' melt(data, id.vars, measure.vars, = "variable", ..., na.rm = FALSE, = "value",factorsAsStrings = TRUE) ### Default(vector) S3 method: melt(data, ..., na.rm = FALSE, = "value") ###

c# Slice Programming 2019-04-06
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kaldi Learning Notes 2019-04-06
error 4/4 failed, log is in exp/make _ mfcc/train/make _ mfcc _ train. *. log Open the make_mfcc_train.1.log file and found: bash: line 1: copy-feats: command not found bash: line 1: compute-mfcc-feats: command not found Resolution: Only kaldi was downloaded, not many libraries were installed, so these libraries should be installed.Mainly wget, installation method (cd to tools inside first): $ brew install wget --with-libressl $ sudo chown -R $(whoami)

selenium and webdriver 2019-04-06
selenium 2 = selenium 1.0 + webdriver. selenium and webdriver

win10 installation of theano and keras 2019-04-06
Originally it was easy to install theano and keras under ubuntu, but since there are still more window systems in common use, there is no way. Although it is more troublesome, we are still trying to install successfully under window.The reference blog links are as follows Because of some problems introduced by these blogs, I rearranged them as follows 1. Install Anaconda (installer) (Python) It is strongly recommended that everyone install Anaconda (installer).

# # Learn more about theano and kears Installation Summary Complete Edition 2019-04-06
in-depth learning theano and kears installation summary full version 1. Premise: A. I am using windows7 64-bit system B.kkears currently only supports python2.7-3.5 (so none of these versions are useful) 2. Preparations: A. If you deleted python version 2.7-3.5, you need to download other Python versions at this time, but it is recommended that you install Anacodna;;Anacodna is extremely convenient and contains all the packages required to install theano.And after downloading Anacodna, there is no need to download python!

10 interesting open source projects on artificial intelligence and machine learning 2019-04-06
GraphLab GraphLab is a new parallel framework for machine learning.GraphLab provides a complete platform for organizations to use extensible machine learning systems to build big data to analyze products. The company's customers include Zillow, Adobe, Zynga, Pandora, Bosch, ExxonMobil, etc. They capture data from other applications or services, and transform the big data concept into predictive applications that can be used in production environment through system modes such as recommendation system, fraud monitoring system, emotion and Social Network Analysis system.