Building a successful machine learning model is no mean feat. It involves an arduous model-building phase and what comes next requires another rigor of maintaining the model output quality. A machine learning model once trained cannot live up to the changing data...
The retail industry has always been at the forefront of innovation. It started with the massive pivot of the customers from the brick and mortar to online shopping. Covid has further exacerbated this shift as is evident in the change in consumer preferences and buying...
Nearly one-third of enterprises admit they don't use AI-based solutions. Tackling the data, tech and deployment-related challenges in a large company can be overwhelming, but not impossible. Filipa Castro, Data Scientist at Continental shared some good practices with...
AI is everywhere and its rate of adoption has significantly increased since the digital acceleration seen through the usher of the covid period. But the aesthetics get worn out soon as the aspiring AI/ML projects do not live up to the potential and end up...
If you are planning to choose machine learning for your business problem assuming its predictions are always correct, then there is something you should know. Machine learning algorithms are probabilistic by nature and are not perfectly accurate. Then what should we...
The role of customer experience is vital and known for a long time. According to the data gathered by CGS, 30% of customers are willing to pay more for excellent service. This can be delivered by listening to the voice of customers and constantly monitoring their...
Virtual communities make a difference, especially during a pandemic where people are unable to meet and interact in person. Slack is a real gold mine when it comes to finding inspiring peers who share similar data science joys and challenges. That’s why we have put...
Machine learning models can undoubtedly help humans make more informed decisions, with an increasing number of use cases among different industries. By feeding the algorithms with large amounts of data, they are able to identify patterns and make predictions...
Cybersecurity and AI are both complex enough on their own, but what are the possibilities and challenges when these two fields collide? With data continuously growing, a lack of talent, and increasing threats from digital attackers, the need for AI and machine...
Machine Learning (ML) is being applied successfully across many industries and by all kinds of organizations, from start-ups to large corporations. However, many encounter unexpected problems when trying to apply ML to their use case. In this post, we are going to see...