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Name: Sankalp Gilda
Type: User
Bio: Machine Learning Engineer | Ph.D., Astronomy
Twitter: astrogilda
Location: Gainesville, FL
Name: Sankalp Gilda
Type: User
Bio: Machine Learning Engineer | Ph.D., Astronomy
Twitter: astrogilda
Location: Gainesville, FL
Source code for Algorithmic Trading with Python (2020) by Chris Conlan
Antialiasing cnns to improve stability and accuracy. In ICML 2019.
Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.
Repository for "Fitting a Kalman Smoother to Data"
A curated list of resources for Learning with Noisy Labels
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
TensorFlow - A curated list of dedicated resources http://tensorflow.org
A graph-based functional API for building complex scikit-learn pipelines.
Model Serving Made Easy
Black Box Quantiles for Kernel Learning
This repository provides the code for replicating the experiments in the paper "Building One-Shot Semi-supervised (BOSS) Learning up to Fully Supervised Performance"
Python Framework to calibrate confidence estimates of classifiers like Neural Networks
Scrape candlestick data from crypto exchanges and upload it to Kaggle.
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
Automation scripts for compute canada
Cramer-Wold AutoEncoder
Repository for the paper "An Adversarial Approach for the Robust Classification of Pneumonia from Chest Radiographs"
Deep Adaptive Input Normalization for Time Series Forecasting
slidedeck for "Techniques in Time Series Analysis for Machine Learning Enthusiasts"
Keras ensembles, made easy.
Source code and data for the paper "Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors"
Small Data Challenge: Structural Analysis and Optimization of Convolutional Neural Networks with a Small Sample Size - UPMC (University Of Pittsburgh)
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
PyTorch GPU implementation of the ES-RNN model for time series forecasting
scikit-learn inspired extensions for machine learning
Collection of notebooks about quantitative finance, with interactive python code.
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.