Category Archive: Python

Open a World of Opportunities: Web Scraping Using PHP and Python

The latest estimates says, the total number of websites has crossed one billion mark; everyday a new site is being added and removed, but the record stays.

Open a World of Opportunities: Web Scraping Using PHP and Python

Having said that, just imagine how much data is floating around the web. The amount is so huge that it would be impossible for even hundreds of humans to digest all the information in a lifetime. To tackle such large amounts of data, you not only need to have easy access to all the information but should also process some scalable way to gather data in order to organize and analyze it. And that’s exactly where web data scraping comes into picture.

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The Timeline of Artificial Intelligence and Robotics

The Timeline of Artificial Intelligence and Robotics
 

Cities have been constructed sprawling over the miles, heaven-piercing skyscrapers have been built, mountains have been cut across to make way for tunnels, and rivers have been redirected to erect massive dams – in less than 250 years, we propelled from primitive horse-drawn carts to autonomous cars run on highly integrated GPS systems, all because of state-of-the-art technological innovation. The internet has transformed all our lives, forever. Be it artificial intelligence or Internet of Things, they have shaped our society and amplified the pace of high-tech breakthroughs.

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Let’s Make Visualizations Better In Python with Matplotlib

Learn the basics of effective graphic designing and create pretty-looking plots, using matplotlib. In fact, not only matplotlib, I will try to give meaningful insights about R/ggplot2, Matlab, Excel, and any other graphing tool you use, that will help you grasp the concepts of graphic designing better.

 
Let’s Make Visualizations Better In Python with Matplotlib

Simplicity is the ultimate sophistication

To begin with, make sure you remember– less is more, when it is about plotting. Neophyte graphic designers sometimes think that by adding a visually appealing semi-related picture on the background of data visualization, they will make the presentation look better but eventually they are wrong. If not this, then they may also fall prey to less-influential graphic designing flaws, like using a little more of chartjunk.

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Facebook is planning to evaluate its quest for generalised AI

A major misconception about artificial intelligence is the fact that today’s robots possess a very generalized intelligence, however, we are fairly efficient in leveraging large datasets to accomplish otherwise complex tasks. Nevertheless we still fail and fall flat at the prospect of replicating the breadth of human intelligence.

 
Facebook Artificial Intelligence Researchers
 

Care to contribute to AI development in today’s world? Then take up a Machine Learning course online with us. But in order to move forward a generalized intelligence, Facebook is ensure that we know how to evaluate the process. In a recently released paper, Facebook’s AI research (FAIR) lab has outlined just that as a part of its CommAI framework.

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Here Are Four Predictions For AI This 2017!

Last year was the year, which saw artificial intelligence, went mainstream.

 

Here Are Four Predictions For AI This 2017!

 

By that, we do not mean just getting filtered raunchy photos on Twitter or getting the fake news suggestions on Facebook.

Here is what to look for in Artificial Intelligence for this New Year:

  • Driven by unprecedented financial support (along with a growing open source ecosystem), founders have been delivering artificial intelligence start-ups at a record high rate.
  • GE, Google, Intel, Microsoft, Facebook, Apple, Salesforce and Samsung, and several other name brands made rigorous AI investments last year.
  • There are now five million homes, which, are talking about their music and shopping choices with the help of Alexa from Amazon.
  • There is a whole new department of U.S. Department of Transportation Committee for self-driving cars. Even a few years ago, there were people talking about 2025 or so for the accessibility of self-driving cars (of level 5 autonomy), but this is a reality now, much before we could reach 2020. It is also amazing to think that self-driving cars may whittle down the 1.2 million annual deaths from automobiles.
  • Also in other interesting news, two AI unicorns just grew their horns, the Cylance in Silicon Valley and iCarbonX in China.
  • Also more than one-fifth of the MIT 50 smartest companies list, include AI as a core approach these days.
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The Choice Between SAS Vs. R Vs. Python: Which to Learn First?

It is a well-known fact that Python, R and SAS are the most important three languages to be learnt for data analysis.

 

The Choice Between SAS Vs. R Vs. Python: Which to Learn First?

 

If you are a fresh blood in the data science community and are not experienced in any of the above-mentioned languages, then it makes a lot of sense to be acquainted with R, SAS or Python.

 

Does that sound too difficult? Do not fret, by the time you are done reading this post you will know without a doubt which language is the right one for you to take up first.

 

Introduction to the languages:

  • R programming: R is the lingua franca for statistics. It is an open source programming language, free to access and pen to all to perform data analysis tasks.
  • Python: this is a multi-purpose, open source programming language, which has become a very popular one these days in data science due to its vibrant community and immense data mining libraries.
  • SAS: SAS is currently the undisputed market leader when it comes to enterprise analytics space. It provides a huge array of statistical functions; it has a good GUI for people to pick it up faster and also offers a well-backed tech support team.

 

You must be aspiring to start a career in data science for gaining some knowledge and to be able to transition to this field in the near future. And if so, then some research on your part is necessary to understand what you must take up as your first lesson to excel in this complex field. It will help up your chances of landing the right job. But the question here remains – whether you should take up R? Or should it be better to make SAS a priority for learning? Or should one learn Python instead?

 

Here are the factors that one should consider, before deciding what to learn:

Industries where the tool is used the most:

An international HR firm Burtch Works, asked about 1000 quantitative professionals about which language they prefer better – is it SAS, R or Python. The survey results, came out to be something like this:

 

SAS vs R vs Python

Image Source: kdnuggets.com

 

 

big companies mostly prefer SAS, because they offer better customer services, this is also the reason why SAS has an advantage within the financial services sector and the marketing companies, where the budget is not a concern for selecting the tool.

 

 

Tools used in data science industry

Image Source: kdnuggets.com

On the other hand, start-ups and mid-sized firms use R and Python. Tech as well as telecom companies also require a large amounts of unstructured data to get analyzed, and hence, many data scientists associated with these sectors use machine learning techniques for which Python and R are more suitable.

 

Data Scientist vs Predictive Analytics

Image Source: KDnuggets

You can take up an R programming course in Gurgaon with DexLab Analytics.

The ease of learning, and pocket pinch:

The language SAS is an expensive software used for commercial purposes and is mostly used by large corporations with massive budgets.

 

However, R and Python are free software, which can be used and downloaded by anyone keen on learning.

 

No prior knowledge in programming is required by people for learning SAS, as it has simple GUI, which is easy to use. There is the provision of parsing SQL codes, combining it with macros along with other native packages it makes learning SAS a cakewalk for those with basic knowledge of SQL.

 

For analyzing data in Python one will need data mining libraries like Pandas, Scipy, and Numpy. In other words, one will not code in a native Python language for data analysis. The codes one writes in these abovementioned libraries are somewhat similar to those in R. So, it is easier for people to learn Python who are already aware of R in data science. For those who already know R it is recommended that they learn the basics of Python Programming language before one starts to learn the Python data mining ecosystem.

Capabilities in data science:

SAS is very efficient at sequential data access and for database access through using SQL which is well integrated. With the drag-and-drop interface, it makes it easier for people to create better statistical models faster.

 

R is best known for in-memory analytics and is mainly used when the data analysis tasks need standalone servers. It is a great tool for exploring data.

 

Python libraries like Numpy, Pandas, Scipy and Scikit-learn allows it to be the second most popular programming language in the field of data science right behind R. One can also create a lot of beautiful graphs and charts with libraries like Seaborn and Matlplotlib.

 

Get R programming certification to pave your way to data science success with our courses from DexLab Analytics.

Community support:

R and Python have a huge community support online from things like mailing list, Stackover flow and other user-contributed documentations and codes.

 

SAS also has an online active community which is regulated by the community managers.

 

So advance your career with a course on Machine Learning using Python or R programming.

 

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

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Python Vs R- Which You Want To Learn First

If Big Data interests you as a career choice and you are pretty much aware of the skills you need in order to be proficient in this field, in all likelihood you must be aware that R and Python are two leading languages used for analyzing data. And in case you are not really sure as to learn which of the mentioned articles first, this post will help you in making that decision.

 
Python Vs R- Which You Want To Learn First
 

In the field of analysis of data, R and Python both are free solutions that are easy to install and get started with. And it is normal for the layman to wonder which to learn first. But you may thank the heavens as both are excellent choices.

 

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