Blog

Blog Categories

Introduction Exploratory data analysis (EDA) is an approach to data analysis to summarize the main characteristics of data. It can be performed using various methods, among which data visualization takes a great place. The idea of EDA is to recognize what information can data give us beyond the formal modeling or hypothesis testing task. In other words, if initially we don’t have at all or there are not enough priori ideas about...
In the modern world, the information flow which befalls on a person is daunting. This led to a rather abrupt change in the basic principles of data perception. Therefore visualization is becoming the main tool for presenting information. With the help of visualization, information is presented to the audience in a more accessible, clear, visual form. Properly chosen method of visualization can make it possible to structure large data arrays,...
The more carefully you process the data and go into details, the more valuable information you can get for your benefit. Data visualization is an efficient and handy tool for gaining insights from data. Moreover, you can make the data far more understandable, colorful and pleasant with the help of visualization tools. As data is changing every second, it is an urgent task to investigate it carefully and get the insights as fast as...
What is Exploratory Data Analysis Exploratory data analysis (EDA) is a powerful tool for a comprehensive study of the available information providing answers to basic data analysis questions. What distinguishes it from traditional analysis based on testing a priori hypothesis is that EDA makes it possible to detect — by using various methods — all potential systematic correlations in the...
Since the dawn of the digital age, the amount of data stored on servers has risen dramatically. More and more firms are looking for talent that can handle their datasets and generate insights for business decisions. Data scientists are among the most popular for this task. Google Trends shows that the global volume of the search term “Data Scientist” has tripled over the last 5 years - but how does the increasing demand translate...
Since the dawn of the digital age, the amount of data stored on servers has risen dramatically. With this increase, more and more firms are looking for talent that can handle their datasets and generate insights for business decisions. Google Trends shows that the global volume of the search term “Data Analyst” nearly tripled over the last 5 years. How does the increasing demand translate into earnings of data analysts in...
Companies use machine learning to improve their business decisions. Algorithms select ads, predict consumers’ interest or optimize the use of storage. However, few stories of machine learning applications for public policy are out there, even though public employees often make comparable decisions. Similar to the business examples, decisions by public employees often try to optimize the use of limited resources. Algorithms may assist...
Are you looking for real world data science problems to sharpen your skills? In this post, we introduce you to four platforms hosting data science competitions. Data science competitions can be a great way for gaining practical experience with real world data, and for boosting your motivation through the competitive environment they provide. Check them out, competitions are a lot of fun! Kaggle Kaggle is the best known platform...
Curious about neural networks and deep learning? This post will inspire you to get started in deep learning. Why are we witnessing this kind of build up for neural networks? It is because of their amazing applications. Some of their applications include image classification, face recognition, pattern recognition, automatic machine translation, and so on. So, let’s get started now. Machine Learning is a field of computer science that...
The open-source project R is among the leading tools for data science and machine learning tasks. Given its open-source framework, there are continuous contributions, and package libraries with new features pop up frequently. Currently, the CRAN package repository features 12,525 available packages. This post takes a look at the most popular and useful packages that have set the standards for solving data manipulation, visualization, and...
  Currently, Python and R are the dominating data science tools and Python will probably even be taking the lead (at least based on the latest KDNuggets survey ). When did the two open source players manage to become the leading platforms for analytics, data science, and machine learning, leaving behind established players such as Matlab or SAS? Here are some insights from Google Trends. Looking at the years 2009 - 2013 in the...
For individuals, businesses and research institutes working with emerging technologies, it is important to follow and shape societal debates revolving around their field. Sooner or later, societal debates are likely to translate into political action, which may greatly impact work on emerging technologies – for better or worse. Also, if research institutes and businesses aim for more than research results and profit, they’re...