An Image Data based perspective on Data Science, Machine Learning and Deep Learning

Recent times have observed frequent usage of terms like data science, machine learning and deep learning and that too interchangeably in most of the cases. Nevertheless, these terms are probably not to be used loosely for defining a problem in the domain and careless usage may lead to misleading outcomes which in turn is highly frustrating. Popular applications like Google Lens, CamFind etc.  are efficiently using all these techniques to generate business revenue. These applications are based on analysis of content based image data. This talk has attempted to identify the key differences among these terminologies, namely, data science, machine learning and deep learning with special thrust on application of these techniques in the domain of content based image data.  The talk is a walk through for designing scalable techniques with content based image data which is in abundance and the most used mode of communication these days.

Hence, the talk distinctively includes:

• Significance of Data Science, ML and DL

• Differentiation of the concepts

• Resourceful usage of image data

• Usage of Data Science in Image Processing

• Applications of Image Processing in Data Science, ML and DL

• Interdisciplinary approaches in ML/DL with image data