The differences between machine learning and statistics Machine learning and statistics are the two core disciplines for data analysis. Both fields provide the scientific background for data science and data scientists will usually have trained in one of the two. However, much has been said about the differences between the two disciplines, while there are proponents only of … [Read more...] about Statistics vs Machine Learning: The two worlds
machine learning
The Future of Robotics and Automation: All You Need to Know
Robotic assistants, driverless autos, and future machinery were only tantalizing clues of what was to come in old sci-fi films. But over the course of a few decades, truth has supplanted imagination. Automation and robotics are now at the forefront of technology, ushering in a time when machines can complete activities that formerly required human touch and understanding. What … [Read more...] about The Future of Robotics and Automation: All You Need to Know
Nobody Should Blindly Trust AI. Here’s What We Can Do Instead
Years from now someone will write a monumental book on the history of artificial intelligence (AI). I'm pretty sure that in that book, the early 2020s will be described as a pivotal period. Today, we are still not getting much closer to Artificial General Intelligence (AGI), but we are already very close to applying AI in all fields of human activity, at an unprecedented scale … [Read more...] about Nobody Should Blindly Trust AI. Here’s What We Can Do Instead
The Impact of Quality Data Annotation on Machine Learning Model Performance
Quality data annotation services play a vital role in the performance of machine learning models. Without the help of accurate annotations, algorithms cannot properly learn and make predictions. Data annotation is the process of labeling or tagging data with pertinent information, which is used to train and enhance the precision of machine learning algorithms.Annotating … [Read more...] about The Impact of Quality Data Annotation on Machine Learning Model Performance
Unleashing Data Science Efficiency: 5 ModelOps Capabilities That Drive Productivity
ModelOps plays a crucial role in operationalizing and managing machine learning models in production. By implementing specific capabilities, data science productivity can be significantly enhanced. In this article, we will explore five ModelOps capabilities that can boost data science productivity.1. Automated deploymentMoving ML models from development to production more … [Read more...] about Unleashing Data Science Efficiency: 5 ModelOps Capabilities That Drive Productivity
