In this we used CNN to classify various videos into their respective categories

Technology Stack: MATLAB, Deep Neural Network, Convolution Neural Network, Support Vector MachineStep 1: We made test data set comprises of videos from various categories (Forest, cars, dance etc..)Step 2: The approach is to extract features from the data set which are pre-trained by using Convolution Neural Network (CNN) extracted features are kept in a particular matrix.Step 3: Video from test data set is picked randomly and feature matrix is calculated than matrix formed by trained data set and from randomly picked video is compared.By this method we get 95.6% of accuracy.

Technology Stack: IBM Cloud, Java, J2EE, XML, HTML 5, CSS 3, JSP, DB2Created front end web application using HTML 5 and CSS 3Used J2EE on Eclipse to connect front end web application to databaseCreated a clone of table structure on IBM Cloud

https://medium.com/analytics-vidhya/introduction-to-neural-networks-and-activationfunctions-58e2 6887c52d

https://medium.com/@akshaykr.sharma19966/maps-with-python-using-folium-ab4ccff84cbd

https://akshayblogging.home.blog/2018/12/14/confidence-interval/