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In this project, I build, train, validate, and test a neural network from scratch using the popular Bike-Sharing dataset to predict daily bike rental ridership.
Python 2.06%
Jupyter Notebook 97.94%
bike-sharing-ml's Introduction
Information Systems Grad @ Carnegie Mellon University | open to freelance work & new opportunities
Extensive coursework & background in: Machine Learning, Software Engineering
Previously: Boeing, Apple, In-Q-Tel
Machine Learning Engineer intern @ ๏ฃฟ (2 x @ ๏ฃฟ)
๐ญ Previously worked as a Machine Learning Engineer and Software Development Engineer intern with geospatial computer vision ML models @ In-Q-Tel, a venture capital firm that delivers cutting-edge technologies to the CIA and other US Government agencies
๐ญ Researching: multi-agent reinforcement learning, graph neural networks, zero-shot dependency parsing
๐ฑ Frequent competitor on Kaggle
๐ฑ Areas of Interest: Computer Vision, Natural Language Processing techniques, Deep Reinforcement Learning
๐ฌ Open to collaborate on or discuss Machine Learning papers/problems/projects
๐ซ Reach me at: roshan.ram0101 [at] gmail.com
Using Neural Network to Create Bike-Sharing Predictions
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Using XGBoost, Deep Learning to Predict Insurance Claims (Kaggle Competition, Capstone Project)
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Natural Language Processing:
Creating TV Captions/Scripts with RNNs
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Hidden Markov Models for Part-of-Speech (POS) Tagging
RNNs for Machine Translation
RNNs for Text Sentiment Analysis
Applying RL to Solve Frozen-Lake Environment Problem
Applying RL to Create A BlackJack AI
Applying RL to Solve Cliff-Walking Environment Problem
Applying RL to Solve OpenAI's Taxi-World Environment Problem
Applying RL to Deep Q-Learning
Applying RL, Deep Q-Learning to Teach A Quadcopter How To Fly
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