A Data Science Leader's Perspective on Getting Value from AI Workloads

Research in Deep Learning started as early as the 1960s, though the term itself was coined in 1986. With accurate predictions becoming the need of the hour, the amount of computing available and the massive data being collected, Deep Learning became the preferred algorithms at least over the last 5 years or so. As the complexity of problems arose, Deep Learning became the answer for problems that involved heavy datasets. A few millions of rows of supervised learning could effectively be crunched by ensemble tree based algorithms itself. However, for problems like computer vision or speech-to- text, deep learning was the answer.