Software Engineer @ Microsoft, IIIT Gwalior
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Multimodal_Meta_Learning_with_Siamese_Network
April 30, 2020 – March 25, 2023
Multi-modal classifications of digits with image and audio modality. One shot learning with Siamese network is used to predict if the given input image-audio pair belongs to same class or not.
View ProjectAndroid-CryptoChatApp
August 19, 2019 – August 19, 2019
Android-CryptoChatApp — GitHub repository
View ProjectFake_News_detection
August 7, 2019 – August 9, 2019
Fake_News_detection — GitHub repository
View ProjectOffline_Signature_Verification
July 15, 2019 – July 20, 2019
Classification of signatures in image format as genuine or fake. Created two models - one from scratch using deep learning layers and other using pre trained model VGG16. Before training used image pre processing techniques as well.
View ProjectTensorflow_Multiclass_Image_Classification
June 20, 2019 – July 10, 2019
Image classification with tensorflow
View ProjectNIST_statistical_test_implementation
June 15, 2019 – June 24, 2019
NIST_statistical_test_implementation — GitHub repository
View ProjectForest_Cover_type-Classification_Technique
June 4, 2019 – June 26, 2019
Forest_Cover_type-Classification_Technique — GitHub repository
View ProjectHouse_Prices-Regression_technique
May 19, 2019 – June 26, 2019
Different Regression Techniques are used for predicting the House Prices. Linear Regression, Random Forest and XG Boost algorithms are used for training
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong focus on personal data science projects, indicating self-motivation and a passion for the field. However, the lack of team-based projects or professional experience makes it difficult to assess collaboration and broader cultural fit within an organizational setting. The projects align well with a Data Scientist role, demonstrating initiative in learning and applying various techniques.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.