Data science platform market is estimated to rise with a CAGR of 31.1% by generating a revenue of $224.3 billion by…

Data science is booming day by day. In the market, the job place is quite saturated.

There are many skills you need to become a data scientist. There is a misconception…

What are the Importances of Data Science in the Modern Age?

Data Science is considered one of the best lucrative job fields of the 21st century. It is nothing other than the combined study of mathematics, statistics & computer science (including domain and programming expertise); which is used to…

Science is a very crucial and important part of our lives nowadays, through which we can solve any difficulties in our lives. However, we only know little about how science has to go through many problems of its own. In order to apply this science…

A Customer's behavioral pattern that includes habits, needs, preferences, and means of interacting with service all comes under consumer behavior. Over the years promoting, customer-centric marketing campaigns have become the norm of major industries. According to the statistics, over 86% of consumers would pay more for getting a better customer…

Data science is study of data that involves emerging methods of recording, storing and analyzing the data, to easily extract the needed information to take the necessary decisions for business. The phrase ‘Data Science Platform’ can be described as a software including a variety of technologies for advanced analytics uses…

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…

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…

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…

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…

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…

Recently Netflix launched Rs 199 ($2.8) mobile-only monthly plan in India. CyberMedia Research (CMR) reported that after the release of the new mobile plan, Netflix now has the potential to reach 3.7 million subscribers as compared to the earlier number of 1.3 million subscribers in India by the end of the year. This increased subscriber count…

We’ve written a lot about finding and preparing data lately. But that’s only the beginning when it comes to extracting value from it. When organizations begin flowing external data through their organization, the various issues associated with data sharing start causing problems. Some of these issues include:

• Controlling permissions and data access, including sharing partial/filtered views or picture-in-picture data
• Accurately tracking changes to data and monitoring how…