
Understanding Data Literacy in the Digital Age
As we have entered the digital era, data and analytics strategies (D&A) have become important, as these technologies can transform any business during a massive data spike. According to global research, it was observed that around 2.5 quintillion bytes of data are produced by IT companies every day; therefore, to understand the importance of data,…

Modernizing Data Management with Data Fabric Architecture
Data has always been at the core of a business, which explains the importance of data and analytics as core business functions that often need to be addressed due to a lack of strategic decisions. This factor gives rise to a new technology of stitching data using data fabrics and data mesh, enabling reuse and…

Kickstart Your ML Journey: Tips for Choosing the Right Course
Introduction Are you ready to dive into the exciting world of machine learning (ML)? As the demand for ML professionals continues to soar, there has never been a better time to kickstart your journey in this dynamic field. Whether you’re a seasoned data analyst looking to expand your skill set or a newcomer eager to…

Bridging the Gap: How AI Can Improve Access to Mental Wellness
With the dawn of the COVID-19 pandemic, mental health has become an area of concern, as more than 1 billion humans every year seek help from clinicians and therapists to cure problems such as depression, anxiety, and suicidal thoughts. This inevitable growing pressure has stretched healthcare and therapeutic institutes to choose smarter technologies such as…

Daniel Langkilde, CEO and Co-founder of Kognic – AITech Interview
To start, Daniel, could you please provide a brief introduction to yourself and your work at Kognic? I’m an experienced machine-learning expert and passionate about making AI useful for safety critical applications. As CEO and Co-Founder of Kognic, I lead a team of data scientists, developers and industry experts. The Kognic Platform empowers industries from…

Unlocking potential: How AI is transforming drug development and material science
In recent years, artificial intelligence (AI) in the pharmaceutical industry has gained significant traction, especially in the drug discovery field, as this technology can identify and develop new medications, helping AI researchers and pharmaceutical scientists eliminate the traditional and labor-intensive techniques of trial-and-error experimentation and high-throughput screening. The successful application of AI techniques and their…

Navigating the Future With the Integration of Deep Learning in Big Data Analytics
In the fast-growing digital world, deep learning (DL) and big data are highly used methods for data scientists. Numerous companies, such as Yahoo, Amazon, and Google, have maintained data in Exabytes, which helps generate large amounts of data with the help of big data analytics and deep learning tools and techniques. Earlier data scientists used…