As data collection is a key concern of the building the ethical machine learning pipeline, it should be framed as an important front-of-mind.
The improved methods of collecting high-quality data, coupled with advancements of machine learning models fueled a new wave of healthcare practices. From retinopathy to computer vision-based surgeries, algorithms have found their ways into critical life-saving domains. The potential is tremendous, but somehow the world is cynical about a total embrace.
Traditional business and technology sectors are not the only fields being impacted by AI. Healthcare is a field that is thought to be highly suitable for the applications of AI tools and techniques.
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You got intrigued by the machine learning world and wanted to get started as soon as possible, read all the articles, watched all the videos, but still isn’t sure about where to start, welcome to the club.
Machine learning is quite an exciting field to study and rightly so. It is all around us in this modern world. From Facebook’s feed to Google Maps for navigation, machine learning finds its application in almost every aspect of our lives. It is quite frightening and interesting to think of how our lives would have been without the use of machine learning. That is why it becomes quite important to understand what is machine learning, its applications and importance.
AI, Machine learning, as its title defines, is involved as a process to make the machine operate a task automatically to know more join CETPA