Java or Python: Which One Should a Data Scientist Learn?

Data science is among the trendiest fields in technology. The demand for data science professionals is huge – so much so that Glassdoor named it the number-one job in America for four consecutive years. Despite the buzz it generates, data science is intimidating for many programmers since it requires a strong mathematical backbone and is unapproachable for mathematicians because of coding prerequisites.

That’s why the discrepancy between demand and supply in data science is vast. There’s a word in the street that, if you want to acquire skills that’ll land you jobs, data science is your best option.

At the start of your data science journey, you will need to choose a programming language to run algorithms. There are many programming languages developers use, such as R, Clojure, Julia, or Scala.

In this post, however, I’d like to compare two languages that lead Stack Overflow’s Top Software Development Languages survey – Python and Java. Let’s discuss the benefits, drawbacks, and applications of these technologies in data science.

#java #python #data-science #programming

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Java or Python: Which One Should a Data Scientist Learn?
Seamus  Quitzon

Seamus Quitzon

1602637135

Learning by Doing: How to Learn Java Basics by Building Your Own Project

Java is not the hardest language to start with. So, it becomes way popular among novice developers joining the ranks of Java coders every single day. If you are reading this blog post, you might be interested in learning Java.

Java is widely used across industry, and especially in the area of Enterprise software, which results in many high paying job opportunities and makes this programming language a common language for newbies. A general promotion of it within colleges and other institutions providing a formal Computer Science education also contributes to its popularity.

However, these are not the only advantages of Java — among other things, it allows you to adopt good practices and makes it way easier to learn other languages in the future. And with no doubt, you can easily learn it if you’re following the right approach. In this post, I am going to share some of them with you.

The Importance of Practice in Programming

Beyond all doubt, practice is important and valuable. But, before we get to the advantages of hands-on experience, I want to draw your attention to one essential thing I often tell my students.

New programmers who are just learning and start implementing things, without being supervised, often end up adapting bad practices. To avoid that, especially when you are making your first steps in programming, I recommend looking for a person who will supervise you and teach you. A strong mentorship with someone engaged in a serious project, as well as communication within the community in the form of sharing code and asking for feedback, is worth the effort. Similarly, when you are applying for your first job, you want to be looking for a company with a strong team and a good leader who would be keen on investing into your learning.

Now, let’s return to practical experience. Learning by doing is different from learning by passively consuming the information. To make sure we can use all the newly acquired technology, we should put our skills to test and write tons of code. The benefits of hands-on experience are almost endless.

Efficiency and Productivity

By practicing, you get a clear understanding of what programming is. Consequently, you start doing better with each new hands-on task, complete it faster, and thus become more productive.

Even if you are not working on real-world projects yet, it’s important to get used to having deadlines. They are inextricably linked to the programming process. My recommendation is to set up your own deadlines while practicing stage and follow them as closely as possible.

#java #learn java #java code #learn java in easy way #learn java course #learn java development

Tyrique  Littel

Tyrique Littel

1600135200

How to Install OpenJDK 11 on CentOS 8

What is OpenJDK?

OpenJDk or Open Java Development Kit is a free, open-source framework of the Java Platform, Standard Edition (or Java SE). It contains the virtual machine, the Java Class Library, and the Java compiler. The difference between the Oracle OpenJDK and Oracle JDK is that OpenJDK is a source code reference point for the open-source model. Simultaneously, the Oracle JDK is a continuation or advanced model of the OpenJDK, which is not open source and requires a license to use.

In this article, we will be installing OpenJDK on Centos 8.

#tutorials #alternatives #centos #centos 8 #configuration #dnf #frameworks #java #java development kit #java ee #java environment variables #java framework #java jdk #java jre #java platform #java sdk #java se #jdk #jre #open java development kit #open source #openjdk #openjdk 11 #openjdk 8 #openjdk runtime environment

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Arvel  Parker

Arvel Parker

1593156510

Basic Data Types in Python | Python Web Development For Beginners

At the end of 2019, Python is one of the fastest-growing programming languages. More than 10% of developers have opted for Python development.

In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.

Table of Contents  hide

I Mutable objects

II Immutable objects

III Built-in data types in Python

Mutable objects

The Size and declared value and its sequence of the object can able to be modified called mutable objects.

Mutable Data Types are list, dict, set, byte array

Immutable objects

The Size and declared value and its sequence of the object can able to be modified.

Immutable data types are int, float, complex, String, tuples, bytes, and frozen sets.

id() and type() is used to know the Identity and data type of the object

a**=25+**85j

type**(a)**

output**:<class’complex’>**

b**={1:10,2:“Pinky”****}**

id**(b)**

output**:**238989244168

Built-in data types in Python

a**=str(“Hello python world”)****#str**

b**=int(18)****#int**

c**=float(20482.5)****#float**

d**=complex(5+85j)****#complex**

e**=list((“python”,“fast”,“growing”,“in”,2018))****#list**

f**=tuple((“python”,“easy”,“learning”))****#tuple**

g**=range(10)****#range**

h**=dict(name=“Vidu”,age=36)****#dict**

i**=set((“python”,“fast”,“growing”,“in”,2018))****#set**

j**=frozenset((“python”,“fast”,“growing”,“in”,2018))****#frozenset**

k**=bool(18)****#bool**

l**=bytes(8)****#bytes**

m**=bytearray(8)****#bytearray**

n**=memoryview(bytes(18))****#memoryview**

Numbers (int,Float,Complex)

Numbers are stored in numeric Types. when a number is assigned to a variable, Python creates Number objects.

#signed interger

age**=**18

print**(age)**

Output**:**18

Python supports 3 types of numeric data.

int (signed integers like 20, 2, 225, etc.)

float (float is used to store floating-point numbers like 9.8, 3.1444, 89.52, etc.)

complex (complex numbers like 8.94j, 4.0 + 7.3j, etc.)

A complex number contains an ordered pair, i.e., a + ib where a and b denote the real and imaginary parts respectively).

String

The string can be represented as the sequence of characters in the quotation marks. In python, to define strings we can use single, double, or triple quotes.

# String Handling

‘Hello Python’

#single (') Quoted String

“Hello Python”

# Double (") Quoted String

“”“Hello Python”“”

‘’‘Hello Python’‘’

# triple (‘’') (“”") Quoted String

In python, string handling is a straightforward task, and python provides various built-in functions and operators for representing strings.

The operator “+” is used to concatenate strings and “*” is used to repeat the string.

“Hello”+“python”

output**:****‘Hello python’**

"python "*****2

'Output : Python python ’

#python web development #data types in python #list of all python data types #python data types #python datatypes #python types #python variable type

Ray  Patel

Ray Patel

1625843760

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

  • revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
  • microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
  • Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services