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followers: 2.0 following: 7.0 repos: 16.0 gists: 0.0

Name: Domenico Ceresa

Type: User

Company: BPM LLP

Bio: Data Analyst at BPM LLP with a BS in Data Science and Economics with minors in Computer Science and Math from The University of Oregon

Blog: https://www.linkedin.com/in/domenico-ceresa/

Hi there 👋

My name is Domenico but you can call me Nico, I have a degree in Data Science and am passionate about all things Machine Learning!

🔭 I’m currently working on SubText: a model that takes in the url of a subreddit post and uses a summarization model to extract key information, saving you time in finding the information you need to assist you in what you are working on
⚡ I recently built a Deep Learning model that uses Super Resolution to upscale images up to 4x! I implemented this paper and achieved results within 2db of the paper's results! To see my work, click here
🌱 I’m currently learning everything I can on Deep Learning and AI by building projects, making sure my fundamentals stay up to par, and reading academic papers that shape the future of ML
📫 How to reach me:
Email -> [email protected]
LinkedIn -> https://www.linkedin.com/in/domenico-ceresa/
😄 Pronouns: He/Him

Domenico Ceresa's Projects

100-pandas-puzzles

100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

beijing_pollution_forecast

Uses an LSTM recurrent neural net model to predict the polution in beijing

class-proj-cardiovascular-disease

class-proj-movie-classifier

Classify movies as either a thriller or a comedy based on the frequency of specific words

diamond_league_project

scrapes the diamond league website for stats and creates predictions based on those stats

first-contributions

🚀✨ Help beginners to contribute to open source projects

fsrcnn-2016

Implimentation of the 2016 Fast Super Resolution CNN Paper

fsrcnn-pytorch

PyTorch implementation of Accelerating the Super-Resolution Convolutional Neural Network (ECCV 2016)

home

The personal website/portfolio template by Hashir Shoaib. Built using React and Bootstrap.

Implimentation of the RegNet paper that proposes a modification to the ResNet architecture. This modification consists of an addition all convolutional RNN that increases the extraction of spatio-temporal information. The results of this paper are promising as this architecture increases the accuracy by 1.51% on CIFAR-10 and 2.04% on CIFAR-100

tokyo-olympics-etl

End to end ETL project using data from the tokyo olympics

yellow_pages_scraper

scrapes yellowpages for info about restaurants in oakland(can be changed late)

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