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Soumit Panda's Projects

customer-clustering icon customer-clustering

Customer Segmentation K- Means Clustering Problem Statement:¶ To identify different segments of customers on the basis of their shopping behaviour to run targeted marketing campaign. Data: Online retail is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail.The company mainly sells unique all-occasion gifts. Many customers of the company are wholesalers. Approach: We will build a RFM clustering to identify different customers.

emotion-detection-by-using-keras-and-cnn icon emotion-detection-by-using-keras-and-cnn

In this project, we will build and train a convolutional neural network (CNN) in Keras from scratch to recognize facial expressions. The data consists of 48x48 pixel grayscale images of faces. The objective is to classify each face based on the emotion shown in the facial expression into one of seven categories (Angry, Happy, Sad, Surprise, Neutral). We will use OpenCV to automatically detect faces in images and draw bounding boxes around them. Once we have trained, saved, and exported the CNN, you will directly serve the trained model to a web interface and perform real-time facial expression recognition on video and image data. Once we have trained, saved we will directly run and detect our facial expression.

fake-news-detection icon fake-news-detection

In this project, I will train a Naive Bayes model to detect fake news from a given news corpus. This project could be practically used by any media company to automatically predict whether the circulating news is fake or not. The process could be done automatically without having humans manually review thousands of news related articles.

image-super-resolution-using-autoencoders-in-keras icon image-super-resolution-using-autoencoders-in-keras

Project on Image Super Resolution using Autoencoders in Keras. In this project,I have used autoencoder and Keras with Tensorflow as its backend to train my autoencoder, and use this deep learning powered autoencoder to significantly enhance the quality of images. That is, our neural network will create high-resolution images from low-res source images.

java-javafx-swing-projects-desktop-application-gui-software icon java-javafx-swing-projects-desktop-application-gui-software

All projects are based on ☕ Java(Swing.All projects are database(MySql) connected📂 and compatible to run is🖥️ Desktop(with .exe)🖱️.All projects have a Graphical User Interface(GUI)👨🏻‍💻 that user can communicate and understand the application easily).

linear-regression-by-gradient-descent icon linear-regression-by-gradient-descent

Here I have implemented the Linear Regression Algorithm from scratch,for minimizing the Cost Function I have used Gradient Descent Technique,using Gradient Descent I found out the best values of the parameters for which the cost function is minimized,by fitting these parameters in our equation of line,we get the best fit line.The Mean Squared Error is only 48.74 which is excellent.

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