dukeprashanth Goto Github PK
Type: User
Type: User
🧑🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Using RL for anomaly detection in NSL-KDD
A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold Network field.
Notebooks about Bayesian methods for machine learning
Building a Bayesian deep learning classifier
How to do Bayesian statistical modelling using numpy and PyMC3
Using Bayesian deep neural networks for classification of histopathological images.
This repository contains implementations and illustrative code to accompany DeepMind publications
Emergence of complex strategies through multiagent competition
Time-series machine learning and embeddings at scale.
Python toolkit for quantitative finance
Introduction to Statistical Modeling with Python (PyCon 2017)
🏅 Collection of Kaggle Solutions and Ideas 🏅
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
The LSTM GAN model can be used for generation of synthetic multi-dimension time series data.
PCA and DBSCAN based anomaly and outlier detection method for time series data.
Open MatSci ML Toolkit is a single framework for prototyping and scaling out deep learning models for materials discovery, built on top of OpenCatalyst, PyTorch Lightning, and the Deep Graph Library.
[CVPR 2023 Highlight] Neural Kernel Surface Reconstruction
Ipython notebooks on various topics
PyData San Francisco 2016 - ARIMA Tutorial
data and abstract for PMDA paper (SciPy 2019)
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Computing on Topological Domains
This repository contains demos I made with the Transformers library by HuggingFace.
Train transformer language models with reinforcement learning.
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.