#computer programmng
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pinkprettycure · 6 months ago
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programmng used to be about Fuckgin the computer. but we can't do that anymore because of woke.
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faebrite · 8 years ago
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New GitHub Pride and Trans Shirts are available on their shopify store for pride month!
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ridhimalhotrablog-blog · 6 years ago
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Is Python THE MOST PREFERRED LANGUAGE FOR Data Science?
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Today, variety of programming languages are available, but choosing which language to learn is very difficult. Some works for software engineering, some for data science, and some for creating games.
There are 2 types of programming level:-
Low level programming language
High level programming language
Low-level programming language is the one understandable language mainly used by computers to perform there operation. This language is faster and and more efficient than high level languages. Like, Machine Language.
Machine Language is consists of binaries which can easily read and execute by the computers. For converting into machine code an assembler is required called assembler software.
 High-level programming language has a strong relation with the details of computer. This programming enables the programmer to create code which is independent of the type of computer. These are more familiar to most of us. Examples like, Python, Java, Ruby, and many more. Most of the programmer use High-level programming languages, including data scientists.
Programming Languages for Data Science
 Python
Today, most of the data professionals are using Python.  As it is a general purpose and dynamic programing language, so Data scientists and programmers like Python.  This seems tobe more preferred for data science over R as it ends up faster than R and also its data manipulation. This language is having good packages for natural language processing and data learning and also object-oriented.
R
This is not an easy language to learn, and most people find that Python is easier. Actually, R beats Python by using the lapply function. R was built by statisticians and reflects this in its operations. Data science applications feel more natural in Python. It is an open source language and software for statistical computing and graphics.
Java
Java is an another general-purpose, object-oriented language. This language is very versatile, being used in embedding electronics, in web applications, and desktop application. Data scientist need Java,and frameworks like Hadoop runs on the JVM. These frameworks constitute of the big data stack. Java have a number of libraries and tools for machine learning and data science, it is easily scalable for larger applications, and it is fast.
Hadoop
Hadoop is a processing framework that manages data processing and storage for big data applications running in clustered systems. This allows storage space for huge amount data with processing power with the ability to handle virtually limitless tasks at once.
SQL (Structured Query Language)
It is a domain specific language used for managing data in a relational database management system. SQL is like Hadoop for managing data, but of data is different. Tables and queries of SQL are tough for every data scientist.
Julia Programming
It is an another high level programming language and also designed for high performance computational science and analysis. For web programmng in both front and back end.  This language is faster for Python because as it was designed to implement mathematical concepts like metrics, algebra. While creating programs Julia provides the speedy development of Python, so, it run fast as C programs.
Scala
It’s a general programming language which provides support to functional programming, object oriented programming. Scala was designed to address many issues of Java. This language has different uses for web applicationhs to machine learning, whereas it covers front end development. The language is known for being measurable for handling big data as well.
In today’s life Python is the one most widely used programming language for data scientists. This language allows the integration of SQL,Tensorflow and many more functions for data science and machine learning. Python has also allows a programmer to create CSV files as output to easily understand data in spreadsheets.
From my view point, newly aspiring data scientists should go for first to learn and become master Python before going for any other programming language.
We NearLearn, provides the Best Machine Learning Training with Python in Bangalore, along with Blockchain Training, Reactjs training, Artificial Intelligence, Data science, Corporate Training, and many more.
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learnpainless-blog · 9 years ago
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Android 6.0 Runtime Permission example (Real Example)
As you know that in API 23 (Marshmallows) new Runtime Permission is added to android development. This feature make App installation more faster than before, because on Android Marshmallows above device your app will not ask for Permission at installation time. Permissions will be granted dynamically to your app when you actually need it. That’s a cool Idea. But if you have existing App and you try to install that app on Android Marshmallows device then your app will install without Permissions as expected but if you try to access Camera, Storage then your app will crash saying “No Permissions etc. Exception”. Because you haven’t yet defined runtime Permissions in your app. So you need to modify your app to ask for Permissions when required.
But maybe you tried adding some codes to make runtime Permission work on your app but you still got crash, then here is simple tutorial to embed runtime Permission in your app.
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