Vaibhav Dange is a Python Developer with 5+ years of experience in building and deploying high-performance web applications and machine learning models. He has a strong background in backend architecture design and RESTful API development.
Successfully delivered AI/ML-driven automation solutions, reducing team size from 300 to 10.
Designed and implemented robust machine learning models for facial recognition.
Developed and optimized RESTful APIs for seamless application integration.
Reduced manual data conversion team size from 300 to 10 by automating the process using AI/ML techniques.
Achieved significant efficiency improvements in digitizing newspaper content and predicting motor speed accurately.
Overview: Developed an innovative system for a US-based leading legal media company to automate article splitting from scanned newspapers. Responsibilities: Implemented OCR and NLP techniques to accurately recognize and extract text from scanned newspaper pages. Developed scripts for text parsing, cleaning, and structuring extracted data. Integrated error-checking and data validation processes to ensure high accuracy and relevance.
Key outcomes:
Reduced manual conversion team size from 300 to just 10 resources by automating the process.
Overview: Developed a robust application for detecting and recognizing faces in images or live video feeds. Responsibilities: Developed and optimized facial detection algorithms using Python and OpenCV. Implemented machine learning models with TensorFlow and Keras for facial recognition. Built REST APIs for seamless integration with other applications.
Key outcomes:
Developed and optimized facial detection algorithms for accurate identification.
Overview: Built a movie recommendation system on a Python Django framework. Responsibilities: Developed and maintained the back-end of the movie recommendation platform using Django and Python. Integrated machine learning algorithms for personalized movie suggestions based on user data.
Key outcomes:
Integrated machine learning algorithms for personalized movie suggestions.
Overview: Developed a system to predict motor speed based on sensor data. Responsibilities: Collected, cleaned, and preprocessed large datasets for training and testing the model. Designed and implemented machine learning algorithms to predict motor speed accurately.
Key outcomes:
Designed and implemented machine learning algorithms that accurately predicted motor speed.
Key outcomes:
Developed and maintained the backend of a movie recommendation platform.
Integrated machine learning algorithms for personalized movie suggestions.
Vaibhav Dange
Python Full Stack Developer