Akshay’s interest in computer science sparked when he was working on a women's safety application aimed towards the women welfare in India. Since then he has been incessantly working on improving his skills. He stumbled upon machine learning then. He has made several open-source contributions in the field of ML and would continue to do so. Akshay made successful prototypes like the autonomous car, alphabet recognition, cancer classification, gesture recognition using learning models. These prototypes showcase the power of deep learning and how he can help your organization implement learning models to solve business cases. His ambition is to make a valuable contribution towards the ML community and leave a message of perseverance and tenacity. Currently, he is working as a software engineer at Symantec, India. Also, he deeply influenced by literature, especially Shakespeare's work.
The advent of machine learning along with its integration with computer vision has enabled users efficiently to develop image-based solutions for innumerable use cases. It's crucial to explain the subtle nuances of the network along with the use-case we are trying to solve. With the advent of technology, the quality of the images has increased which in turn has increased the need for resources to process the images for building a model. The main question, however, is to discuss the need to develop lightweight models keeping the performance of the system intact.
To connect the dots, we will talk about the development of these applications specifically aimed to provide equally accurate results without using much of the resources. This is achieved by using image processing techniques along with optimizing the network architecture.
In this webinar, we will discuss the development of ML applications using computer vision techniques to minimize CPU utilization.