Data is everywhere. Data is in different formats. With the advancement of Hardware and Software capabilities, lots and lots of Information is generated in the form of Images, Videos. Deep Learning lets computers “see” and understand visual content in a way that’s similar to how the human brain processes images. Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Also, with growing data, sometimes we need to leverage the power of Deep Learning Techniques to get most of the data.

Deep learning excels on problem domains where the inputs (and even output) are analog. Meaning, they are not a few quantities in a tabular format but instead are images of pixel data, documents of text data or files of audio data. With the advancement in techniques like CNN, RCNN we can interpret the images and transform images into meaningful insights. High Computation power combined with Deep learning readily available trained weights can be leveraged with wide area of applications like Computer Vision, Image Summary, Image Captioning, Image Classifications are possible now. Also, with CNN techniques we are not good at Face Recognition (where organization uses for Automatic Attendance System), Monitoring Traffic, Automatic Car Identification etc… Application of CNN in medical system has grown in vast majority of areas like analyzing X-Ray images to identify disease or not with more accurate than humans.