Feature Sleuth: Understanding and expediting learning in Convolution Neural Networks using feature maps

Github link Abstract Neural networks are heavily used in image processing and classification. However, understanding the internal workings of neural networks has always been a tricky task. One way to look at how a convolutional neural network (CNN) works is by visualizing the feature maps which are obtained after passing a filter through an image. To better understand these feature maps and their purpose in CNN, we experimented with multiple ways of utilizing these in accelerating and enhancing the training of CNNs.

December 25, 2021

Stock Price Prediction using Sentiment Analyses of Tweets

Github Link Abstract The analysis of the stock market has been very profound among the machine learning community. It is well known that is it not very easy to predict the future stock price of a company. There are a variety of intrinsic and extrinsic factors that might influence the market. Many predictive approaches ranging from statistical models to advanced deep learning models have been developed. Most people use historical price data and other technical measures to analyze the stock movement.