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Always learning
💭
Always learning
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Achievement: YOLOAchievement: Pull SharkAchievement: Arctic Code Vault Contributor

Achievements

Achievement: YOLOAchievement: Pull SharkAchievement: Arctic Code Vault Contributor

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@SterlingAI
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roshanr11/README.md

Roshan Ram

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Personal Website


Contributions Welcome
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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 @  (2 x @ )
  • 🔭 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
  • 🔭 Researching: multi-agent reinforcement learning, graph neural networks, zero-shot dependency parsing
  • 🌱 Frequent competitor on Kaggle
  • 🌱 Areas of Interest: Computer Vision, Natural Language Processing techniques, Deep Reinforcement Learning
  • 💬 Open to collaborate on or discuss Machine Learning papers/problems/projects
  • 📫 Reach me at: roshan.ram0101 [at] gmail.com

Projects:

General ML:

  • Using Neural Network to Create Bike-Sharing Predictions
  • Creating, Training, and Deploying a ML Model on AWS Sagemaker
  • Boston House Price Predictions
  • Interpreting Dermatalogist AI Results
  • Applying PCA, Unsupervised Learning to Learn Customer Segments from Data
  • Titanic EDA, Survival Predictions
  • Using XGBoost, Deep Learning to Predict Insurance Claims (Kaggle Competition, Capstone Project)

Computer Vision:

  • Using CNNs to Create a Dog-Breed Classifier
  • Face Generation Using Generative Adversarial Networks
  • Facial Keypoint Detection
  • Image Captioning with CNNs + RNN/LSTM on MS-COCO Dataset
  • Landmark Detection & Robot Tracking (SLAM)

Natural Language Processing:

  • Creating TV Captions/Scripts with RNNs
  • Deep Neural Networks for Speech Recognition
  • Hidden Markov Models for Part-of-Speech (POS) Tagging
  • RNNs for Machine Translation
  • RNNs for Text Sentiment Analysis

Reinforcement Learning:

  • 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

Other:

Pinned Loading

  1. Deep-Learning-for-Trading-RNN-LSTMs-getRichWithStocks.py Deep-Learning-for-Trading-RNN-LSTMs-getRichWithStocks.py Public

    A predictive platform for stock market prediction, utilizing shallow machine learning algorithms built from scratch such as SLR and MSLR, as well as deep learning methods such as LSTMs + RNNs built…

    Python 2

  2. image-captioning image-captioning Public

    Used deep learning to train a CNN + RNN/LSTM on the MS-COCO dataset to automatically generate captions.

    HTML 1 1

  3. NLP-Machine-Translation NLP-Machine-Translation Public

    HTML

  4. ml-aws-sagemaker-deployment ml-aws-sagemaker-deployment Public

    HTML

  5. ml-gan-faces ml-gan-faces Public

    HTML

  6. RL-Teaching-A-Quadcopter-To-Fly RL-Teaching-A-Quadcopter-To-Fly Public

    HTML 1