Hi 👋, I'm Sparsh Bansal

A resourceful Machine learning enthusiast with excellent analytical skills and a demonstrated commitment to come up with new innovative ideas, seeking a lucrative career in the machine learning industry contributing to make this world a better place.

🌱 I’m currently learning Tableau
💬 Ask me about Machine Learning,Data Science
📫 How to reach me [email protected]

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sparshba's Projects

car-rental-app-ui-flutter

Beautiful Car Rental App UI with support for dark mode. Created by Martin Gogołowicz.

The problem that we will use to demonstrate sequence learning in this tutorial is the IMDB movie review sentiment classification problem. Each movie review is a variable sequence of words and the sentiment of each movie review must be classified.

machine-learning-from-scratch

Implementation of popular ML algorithms from scratch

quora-question-pairs

Quora is a place to gain and share knowledge—about anything. It’s a platform to ask questions and connect with people who contribute unique insights and quality answers. This empowers people to learn from each other and to better understand the world. Over 100 million people visit Quora every month, so it's no surprise that many people ask similarly worded questions. Multiple questions with the same intent can cause seekers to spend more time finding the best answer to their question, and make writers feel they need to answer multiple versions of the same question. Quora values canonical questions because they provide a better experience to active seekers and writers, and offer more value to both of these groups in the long term. Currently, Quora uses a Random Forest model to identify duplicate questions. In this project competition by Kaggle, Kagglers are challenged to tackle this natural language processing problem by applying advanced techniques to classify whether question pairs are duplicates or not. Doing so will make it easier to find high quality answers to questions resulting in an improved experience for Quora writers, seekers, and readers.