Himanshu Chauhan

Results-driven Computer Science undergraduate specializing in Machine Learning and Natural Language Processing (NLP). Skilled in building scalable AI models using Python, TensorFlow, and Scikit-learn, with hands-on experience in hybrid neural networks, recommendation systems, and unsupervised learning pipelines. Strong foundation in data structures and algorithms (C++) and statistical modeling.

Seeking an entry-level role to apply deep learning and predictive analytics skills to real-world problems.

Hybrid Sentiment Analysis Model (NLP)

Architected a hybrid classification pipeline combining logistic regression and artificial neural networks.

• Architected a hybrid classification pipeline combining logistic regression and artificial neural networks, improving the F1-score by 18% on a dataset of 50,000+ user reviews.
• Constructed textual features using TF-IDF and word embeddings, reducing feature dimensionality by 32% while maintaining semantic accuracy.
• Tuned model hyperparameters using cross-validation, decreasing overfitting and improving generalization by 21%.
• Validated model performance using precision, recall, confusion matrix, and ROC metrics.

Topic Modeling System (Unsupervised Learning)

Deployed an unsupervised topic discovery pipeline using latent Dirichlet allocation.

• Deployed an unsupervised topic discovery pipeline using latent Dirichlet allocation on 30,000+ documents, achieving a 0.61 topic coherence score.
• Streamlined NLP preprocessing, including lemmatization, tokenization, and stopword removal, improving topic interpretability by 25%.
• Rendered topic distributions using Matplotlib to enable faster analytical insights.

Content-Based Movie Recommendation System

Formulated a recommendation engine using cosine similarity and metadata filtering.

• Formulated a recommendation engine using cosine similarity and metadata filtering, increasing recommendation relevance by 28%.
• Resolved cold-start scenarios using content-based filtering, reducing user bounce rate by 19% during testing.
• Benchmarked ranking performance using precision and similarity thresholds.

Bachelor of Technology (B.Tech) - Computer Science and Engineering - Lovely Professional University (2022-08 - 2026-08)

Intermediate - Class XII - Mother's Touch Sr. Sec. School (2022)

Matriculation - Class X - Mother's Touch Sr. Sec. School (2020)