A 10x machine learning researcher with 1-2 years of experience in applied research | Author of the Python library ”pycolordetector” | An open source contributor at Voila and an author at Analytics Vidya | Editor of The House of Crypto, a Medium publication | One of the Wikimedia Foundation’s IdeaLab Team members | Have trained 50+ ML models on over 1000+ GB data | Co-founded two start-ups: Doeity and Triple S Community | Have proven my mastery in leadership, entrepreneurship, and research with a background in designing corporate strategies | Completed two corporate projects pending from months in weeks at MOSL in 2018 | Interested in devising a better problem-solving method for challenging tasks, and learning state-of-the-art technologies and tools, if the need arises | Looking for a great enthusiastic team to work with that will provide me with interesting and challenging tasks that I can learn from and contribute to | To know more about me try Googling ”Sunny Singh Doeity” |
In a wide range of subject areas, I have analyzed structured and unstructured data to extract actionable business insights. I love to craft stunning and clever visualizations that illustrate surprising results.
I'm strongly convinced that machine learning models should not go to waste in Jupyter Notebooks. Using my software engineering skills, I've built and deployed AI services which create real business value.
I enjoy public speaking, writing professional articles, sharing my knowledge and discussing diverse topics. Thanks to my training and experience in science communication, I'm able to present complex results to a non-technical audience.
Predicted the future web traffic for approximately 145,000 Wikipedia articles using sequence-to-sequence neural networks
Computed the average life expectancy of people from 100+ countries using the WHO Global Health Observatory Data and the Linear Regression model
Trained an LSTM model using PyTorch and RNNto generate poems in English by providing 15000+ poems as dataset
Created a machine learning model to classify events into "tau tau decay of Higgs boson" versus "background noise"
Created an interactive COVID-19 live dashboard, featured on Voila, using the Johns Hopkins University Dataset