• 🚀 Gen AI-Powered Database Interaction System
  Built a Retrieval-Augmented Generation (RAG)-based application using Flask, LLM, and ChromaDB for seamless NLP-driven database interactions with PostgreSQL and MongoDB, enhancing query efficiency by 50%.

• 📸 Transfer Learning for Multi-Class Image Classification
  Developed a multi-class image classifier using transfer learning with models like EfficientNetB0, ResNet, and VGG16, achieving a validation accuracy of 92.57%.

• 💳 Buy Now, Pay Later
  Designed a predictive model for customer adoption of a "Buy Now, Pay Later" feature in a retail app, integrating data-driven insights to boost conversion rates.

• 🔢 OctMnist Classification
  Developed a deep learning classifier on the OctMNIST dataset, leveraging CNN architectures to achieve high accuracy in digit recognition.

• 🚀 SVHN CNN Optimization
  Optimized a Convolutional Neural Network for the SVHN dataset, reducing inference time while maintaining robust performance on real-world image data.

• 🤖 Therapy.ai
  Created an AI-powered chatbot using natural language processing to provide mental health support and therapy recommendations in a user-friendly interface.

• 📈 Stock Price Prediction Using Reinforcement Learning
  Built a reinforcement learning model to predict stock prices and optimize trading strategies, resulting in enhanced decision-making for market investments.

• 🏭 Reinforcement Learning Warehouse Robot
  Implemented RL algorithms for robotic navigation and task planning in a simulated warehouse environment, improving operational efficiency and route optimization.

• 😊 Sentiment Analysis using LSTM
  Developed an LSTM-based model to analyze sentiment from textual data, achieving robust performance in classifying customer reviews and social media posts.

• ⏱ Time Series Forecasting using LSTM
  Designed an LSTM network for time series forecasting, delivering accurate predictions across various domains including finance and demand planning.

• 🖼 VGG16 vs ResNet18 vs ResNeXt
  Conducted a comparative study on popular CNN architectures (VGG16, ResNet18, and ResNeXt) to evaluate performance trade-offs in multi-class image classification tasks.

• 🦠 Rabies Prediction
  Developed a machine learning model to forecast rabies outbreaks using epidemiological data, aiding in proactive public health planning and intervention.

• Full-Stack Development

• Cloud & DevOps Technologies

• Competitive Programming

✉️ Email: [email protected]
🔗 LinkedIn: Ashutosh Sharan
💻 GitHub: asharan2buff

• 📝 Publication
  Published "Bike Count Sharing Prediction Using Machine Learning" in Ijaresm.

• 🏅 People’s Choice Award
  Won Lam India Hackathon 2021 for building a VR Lab Assistant App (Flutter + Unity3D), earning a $1500 prize.

• 🎗️ Samarpana Marathon
  Raised $50K for martyred soldiers’ families through a student-led campaign.