Data is a goldmine for businesses in this day and age. If you seek to become a data scientist in 2021, you must know what you need.

In this in-depth guide, we will walk you through the six most important checks you must pass to become prepared for a data science career – from the scratch.

We will…

This article was written by Sanjib Sharma.

Markov Chain Monte Carlo based Bayesian data analysis has now become the method of choice for analyzing and interpreting data in almost all disciplines of science. In astronomy, over the last decade, we have also seen a steady increase in the number of papers that employ Monte Carlo…

AI is taking over. In 2021, we’re going to see machine learning taking on a bigger role in data analysis as algorithms become capable of reducing error and producing more accurate models within themselves. These algorithms cover iterative processes, decision trees as well as multi-dimensional splitting of datasets. Machine learning is enabling data analysts to have new and greater insights, affecting everything from marketing departments to the way we learn. Here are the essential machine…

To all Data Analysts big and small:

Many Corporates typically have Self service BI and DWH solutions ( I am asking only about those

who did NOT build an inhouse solution) : 

-When is programming needed in most leading Self Service configurations?

-When do analysts and Business executives require coding and programming when the Self…

11 Nov, 2020, Washington D.C.: Since the launch of the World Data Science Initiative (WDSI) in January of 2020 institutions in more than 20 countries have applied to be a part of the initiative, which is the world’s biggest ever talent development project in Data Science. The African continent can now boast its first institution to join the initiative; University of Rwanda.…

Data science uses algorithms, tools, and technologies to identify patterns in data and eventually glean valuable insights from the raw data. Simply put, it allows us to make sense of all that abundance of data that we seem to have all around us. We don’t have to tell you why data science has quickly gained popularity globally, with more and more companies and enterprises seeking to integrate it into their operations. It is by undertaking the development of relevant tools and software, of…

Cloud has been the most significant technology that has enabled the growth of various businesses of all sizes. It offers numerous benefits without paying any additional cost or making new investments in hardware and infrastructure. Companies today generate vast volumes of data and to drive insights out of this Data, they need to inevitably leverage data analytics. Data analytics helps in driving business growth by enhancing their services and gaining a competitive edge. Larger companies can…

Plenty of new technologies have emerged. Some of them have quickly established themselves to virtually connect us as an integral part of, well, everything we do. One of the most important in this lot of technologies is Big Data. Given that it helps companies gather, store, process, and analyze an extensive amount of data to pursue previously undiscovered insights and details, it is understandable why it would become such a sought-after technology and that too so quickly. It also explains why…

Big data, huh? No matter where you look, there it is! And this seeming omnipresence is not without reason, i.e., the technology does indeed play a vital role in the world today. Defined as an amalgamation of different tools to gather and closely analyze data, big data delivers highly valuable insights and analysis. As you can imagine, this ability has made it highly beneficial to, well, literally every industry and business on the face of Earth. That holds for the manufacturing industry…

In our previous article — 5 Challenges to be prepared for while scaling ML models, we discussed the top five challenges in productionizing scalable Machine Learning (ML) models. Our focus for this…

Machine Learning (ML) models are designed for defined business goals. ML model productionizing refers to hosting, scaling, and running an ML Model on top of relevant datasets. ML models in production also need to be resilient and flexible for future changes and feedback. A recent study by Forrester states that improving customer experience, improving profitability & revenue growth as the key goals organizations plan to achieve specifically using ML initiatives.

Though gaining…

Big data has come to play an essential role across the entire spectrum of industries in the world today, including real estate. In fact, in real estate, this novel technology has an exciting role to play. You see, real estate is inherently complex, thanks to the countless factors involved; there’s the people, the local real estate market, and several other factors that affect it. As a result, it can be quite challenging too, say, determine the right price or rent for a given property.…

Big data analytics in the healthcare industry today is evolving into a promising field for delivering real-time insights from very large data sets. Plus, it also helps improve outcomes while reducing costs.

The trending digitization is leveraging the potential of data analytics and business intelligence.

According to Industry experts, the AI health market is to…

Introduction:

Here’s a fun fact; An average human being (probably an adult) makes close to 30,000 conscious decisions every day. This isn’t entirely true though, in fact, I just made that number up. I could be right because if you think about it, how many decisions would you say you make on a day to day basis? Depending on who you are the above obviously varies widely and you know best. We all…

Introduction

Artificial neural networks are based on collection of connected nodes, and are designed to identify the patterns. They are part of deep learning, in which computer systems learn to recognize patterns and perform tasks, by analyzing training examples. For example an object recognition system can be fed to thousands of labeled images of houses, cars, traffic signals, animals etc. and would…

Just about every company worth its salt today uses data and analytics to better understand their customers and better meet their needs.  For some companies, such as Google, Amazon and others, data science is the very foundation of their business model - but these companies use data analytics in service of their broader core mission.  The universe of public companies that actually provide data and analytics solutions is far smaller and harder to define, but includes industry behemoths such as…

In the era of the Internet, the ability to crunch large amounts of data and process it with speed and efficiency has become essential for businesses to survive. But you try sitting down and going through all that data by hand: you'll get done sometime in the year 2050 if you're lucky.

That's where machine learning comes to the rescue. But…

Overview:

This post is about improving the effectiveness of the data science team and improving collaboration between data scientists and stakeholders for better outcomes.  

Aligning goals:

Regardless of the specific project, agreeing on the expected outcomes and goals before beginning the work is a best practice. But with the advent of machine learning (ML) models, it’s for both sides to discuss the critical measures of success for the…