<li><a href="generic.html">Research</a></li>

<h3><b style="font-size: 25px">Key Projects</b></h3>

<p><b style="font-size: 18px;">Monitor the Person Appearance </b><br> Problem Statement: Monitor the person’s attendance. Associate the faces with the existing employee database to identify each employee record the time stamp and date for each employee recognized.

<p><b style="font-size: 18px;">DNA-Splice Gene Prediction</b><br> Each DNA read is a sequence of four [C,A,G,T] types of nucleotides and needs to be converted into numerical representations for machine learning.

<p><b style="font-size: 18px;">Quality Enhancement of Images Using GAN </b><br>

<p><b style="font-size: 18px;">Data Warehouse System </b><br> The problem of this project is that we have to design a scalable data warehouse system that contains various categories and classified image in that categories with no duplication and various different operation. Trained the model on more than 100k images for our data warehouse system and perform different operation on these images. Integrate the whole system in the pipeline and create a GUI and API for the user interface. The accuracy of the system is 99.38 %.

<p><b style="font-size: 18px;">Recommender System</b><br> The problem of this project is that we have to design a recommender system for male & female based on their dressing style and face shape etc. For this project, we have used the detection and classification model. Trained the model on the huge number of label images for our detection and classification model and perform different operation on these detected images. Integrate the whole system in the pipeline and create a GUI and API for the user interface.<br>

<p><b style="font-size: 18px;">Chatbot for Automatic Question Answer</b><br>The problem of this project is that we have to build a chatbot which makes it possible to generate responses based on collections of known conversations. A deep-learning-based solution for the construction of a chatbot off-topic behavior and personality. When confronted with off-topic questions, the bot will try to automatically generate a possibly relevant answer from scratch, based only on a pre-trained RNN model.

<h3><b style="font-size: 25px">Course Projects</b></h3>

<p><b style="font-size: 18px;">Face Shape Type Detector of Human Being</b><br> Implemented a system that analyses various type of face like square, oblong, oval, heart, round and diamond. Dataset gathered from various internet resources and clean the data according to our requirements. Trained the model on more than 10000 labeled images for face shape type detection. The accuracy of system is 84.56%.

<p><b style="font-size: 18px;">Keyword Extraction and Semantic Tag Prediction [KESTP]</b><br>APPLIED SUPERVISED LEARNING METHODS FOR PREDICTING TAGS <br>• Implemented a system that analyses the tags for a question asked by user into appropriate categories.<br>• Data set of Stack overflow dump is used to predict the tags according to user questions.<br>• Applied java sax parser to parse the useful data from data dump.<br>• Applied different classifiers on title ,body and code to predicts the tags.<br>• Used M.L algorithms like SVM , Naive Bayes & Unique Feature Extraction to predict tags.<br>

<p><b style="font-size: 18px;">House Price Prediction-Regression Techniques [HPPRT]</b><br> APPLIED MACHINE LEARNING ALGORITHM <br> • Devised a mechanism to predict the price of each house using stacking of various outputs of regression techniques like lasso and ridge regression, XGboost, elastic net.<br> • This Project is implemented as the part of kaggle competition.

<p><b style="font-size: 18px;">Stock Price Trend Forecasting [SPTF]</b><br>APPLIED SUPERVISED LEARNING METHODS FOR STOCK PRICE TREND FORECASTING <br> • Implemented a system that analyses previous stock data of various <br>companies, processes time-series data and aims to forecast the trends of stock in near future.<br>• Data set of Indian stock market is used to predict the next-minute, next day and next week stock trend.<br>• Applied moving averages,Log normalization techniques for feature generation & selection process.<br>• Used M.L algorithms like SVM & Neural network to predict trend.<br>

<p><b style="font-size: 18px;">Search Engine for 81 GB English Wikipedia Dump</b><br> NFORMATION RETRIEVAL <br>• Implemented inverted index and calculated TF-IDF score.<br>• Retrieving the top 10 results for any query search within 0.3-0.6 seconds.<br>• Supports field search on title, infobox, text, categories.