Becoming a data scientist does not necessarily require a master’s degree. There is a significant shortage of data scientists, and some employers are comfortable hiring people who lack a degree, but have the experience needed. The majority of employed data scientists have a master’s degree, but over 25% do not. If you have the experience, […]
Working Towards Explainable AI
“The hardest thing to understand in the world is the income tax.” This quote comes from the man who came up with the theory of relativity – not exactly the easiest concept to understand. That said, had he lived a bit longer, Albert Einstein might have said “AI” instead of “income tax.” Einstein died in […]
Machine Learning Models for Classification Tasks
In the field of machine learning, regression algorithms and classification algorithms are two important topics that lay a good foundation for people who want to advance their careers in the fields of Data Science or Machine Learning. Regression algorithms are methods that predict a continuous output (e.g., the price of a house), and classification algorithms are methods […]
Using Big Data Analytics to Combat White-Collar Crime
In the era of globalized markets, burgeoning international trade, complex financial systems, ever-evolving compliance and regulatory landscapes, and rapid technology advancement, white-collar crime has unfortunately seen a significant uptick in scale, variety, and sophistication. Whereas white-collar crime used to conjure images of high-flying executives stealing from company coffers, the modern landscape is much more complex, […]
A Brief History of Deep Learning
Deep Learning, is a more evolved branch of machine learning, and uses layers of algorithms to process data, and imitate the thinking process, or to develop abstractions. It is often used to visually recognize objects and understand human speech. Information is passed through each layer, with the output of the previous layer providing input for […]
Why Synthetic Data Still Has a Data Quality Problem
According to Gartner, 85% of Data Science projects fail (and are predicted to do so through 2022). I suspect the failure rates are even higher, as more and more organizations today are trying to utilize the power of data to improve their services or create new revenue streams. Not having the “right” data continues to prevent […]
11 Intriguing Roles for Data Scientists in 2022
Data Science is a diverse field with an array of career and job options out there to pursue. The modern economy is dependent on data and data analysis so, naturally, data scientists are in high demand and enjoy good salary and job security prospects. With that in mind, below are 11 intriguing roles for data […]
How to Use Data Analytics to Gain Valuable Insights with Limited Data
Every modern business professional understands the importance of data. Data can separate the forest from the trees, providing business leaders with a new perspective. From valuable insights regarding customer satisfaction to understanding vital improvements that you can make operationally, data analytics can provide a huge return on investment. However, many businesses shy away from Data Science and analytics because they feel […]
Bringing Data Science into the Organization
In a nutshell, Data Science accelerates business growth. Sudeep Rao, offers solid evidence of this by stating that worldwide nearly $30 billion is invested annually for artificial intelligence (AI) and machine learning (ML) projects. A BI and analytics survey indicated that 94% of the survey participants reported “data and analytics” as important factors for the […]
Will They Blend? Microsoft SharePoint Meets Google Cloud Storage
In the “Will They Blend?” blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source DevOps on the cloud with protected internal legacy tools, SQL with NoSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT sensor data with idle chatting, we’re curious to […]