VINITA SINGH

Self-motivated Data Analyst offering several years of leadership experience across various industries. Methodical with significant experience in data mining and statistical analysis. Excellent problem-solver with history automating processes and driving operational enhancements.

• FashionMNIST Classification using CNN and MLP, Built image classification models from scratch using PyTorch; improved accuracy through architecture optimization.
• High-Dimensional Data Clustering using PCA and Autoencoder, Performed unsupervised clustering on a 9,488×2,000 feature dataset using K-Means, Spectral, and Hierarchical Clustering. Applied PCA and Autoencoder for dimensionality reduction, improving clustering quality and visualization.
• Zipf’s Law Analysis on Indic Corpus, Verified power-law word frequency distributions across Hindi, Assamese, and Bengali using tokenization, frequency analysis, and regression (k ≈ –1).
• Multiclass Text Classification using ML, Deep Learning, and BERT, Implemented traditional ML models (Logistic Regression, SVM) and Deep Learning models (LSTM, CNN). Fine-tuned BERT transformer for improved contextual understanding and achieved high classification accuracy.

• English
• Hindi