yuv4r4j Goto Github PK
Name: Yuvaraj_Ganesan
Type: User
Name: Yuvaraj_Ganesan
Type: User
8th place solution for SIIM-ACR Pneumothorax Segmentation competition on Kaggle
Code for 1st place solution in Understanding Clouds from Satellite Images Challenge.
4th place solution for 2018 Data Science Bowl kaggle competition
Code for a 1st place model in Carvana Image Masking Challenge
Solution to the Google Research - Identify Contrails to Reduce Global Warming Competition
Code for a winning model (3 out of 419) in a Dstl Satellite Imagery Feature Detection challenge
G2Net Competition
Cassava leaf disease classification with CNNs and Vision Transformers (top-1% solution)
Kaggle Salt b.e.s. & phalanx
Code for the TrackML competition on Kaggle
Kaggle Days Paris - Competitive GBDT Specification and Optimization Workshop
some batteries for PyTorch
🚪✊Knock Knock: Be notified when your training ends with only two additional lines of code
The 1st Place Solution of the Google Landmark 2019 Retrieval Challenge and the 3rd Place Solution of the Recognition Challenge.
This is the code for "Learn Machine Learning in 3 Months" by Siraj Raval on Youtube
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
An implementation of the focal loss to be used with LightGBM
LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)
Lime: Explaining the predictions of any machine learning classifier
Code for all experiments.
PyTorch Tutorial at the LOD2021 conference
Code for visualizing the loss landscape of neural nets
Code for the Lovász-Softmax loss (CVPR 2018)
The 4th place and the fastest solution of the Lyft Perception Challenge (Image semantic segmentation with PyTorch)
Data, Benchmarks, and methods submitted to the M4 forecasting competition
Data, Benchmarks, and methods submitted to the M5 forecasting competition
Code and reports from my machine learning classes at USFCA
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.