ML vs Deep Learning : what ’ s the difference ?
ML vs Deep Learning : what ’ s the difference ?
Machine learning and deep learning are often conflated , and with good reason . The whole AI taxonomy is confused , so that companies and individuals use the words they think sound best rather than the ones that best represent what is on offer . Machine learning refers to the ability of software to use relational tools to reach a decision . Oversimplified example : this object is red , that object is red , ergo both these objects may have some relation to one another . Deep learning is layered with multiple layers of machine learning empowering software to eke answers from data that go beyond simple relational computing . However , that doesn ’ t mean simpling adding a second dimension . ‘ This object is red and square , this object is red and circular ’ is still machine learning . ‘ This objects edges are here and they look like a house , this object is here and it looks like a camel ’ is an ( again oversimplified ) explanation . Use cases for deep learning include language and image processing , as well as refined techniques in medical diagnostics and fraud prevention .
“Once business ideas are clearly scoped and road mapped according to their value and feasibility , the next step is to prioritise which data sources to focus ”
ANDRÉ BALLEYGUIER CHIEF DATA SCIENTIST , DATAROBOT
128 September 2021