Anush-Onkar
Msc in Datascience and Artificial Intelligence
Universität des SaarlandesSaarbrücken, Germany
Anush-Onkar's Stars
jwasham/coding-interview-university
A complete computer science study plan to become a software engineer.
shap/shap
A game theoretic approach to explain the output of any machine learning model.
openai/baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
DLR-RM/stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
alexeygrigorev/data-science-interviews
Data science interview questions and answers
rapidsai/cudf
cuDF - GPU DataFrame Library
krishnaik06/The-Grand-Complete-Data-Science-Materials
greyhatguy007/Machine-Learning-Specialization-Coursera
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
openai/mujoco-py
MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.
rbhatia46/Data-Science-Interview-Resources
A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.
jarrekk/Jalpc
🍎Jalpc -- A flexible Jekyll theme, 3 steps to build your website.
paulvangentcom/heartrate_analysis_python
Python Heart Rate Analysis Package, for both PPG and ECG signals
kelvinxu/arctic-captions
sgrvinod/a-PyTorch-Tutorial-to-Super-Resolution
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution
ghimiresunil/LLM-PowerHouse-A-Curated-Guide-for-Large-Language-Models-with-Custom-Training-and-Inferencing
LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing.
yangmingustb/planning_books_1
记录：规划，决策，机器学习，编程的书籍
sgrvinod/a-PyTorch-Tutorial-to-Transformers
Attention Is All You Need | a PyTorch Tutorial to Transformers
foersterrobert/AlphaZeroFromScratch
youssefHosni/Hands-On-LangChain-for-LLM-Applications-Development
Practical LangChain tutorials for LLM applications development
justdjango/django-stripe-tutorial
A tutorial of how to integrate Stripe Payments with Django
Tech-Watt/YOUTUBE-TUTORIAL-CODES
How to Use the Repository You can browse the code for each playlist and episode by navigating to the corresponding folder in the repository. Each folder contains the code used in the video, along with any additional resources, such as data files, images, or configuration files. To use the code, simply clone the repository to your local machine and
MITMediaLabAffectiveComputing/eda-explorer
Scripts to detect artifacts in EDA data
WJMatthew/WESAD
E4 data, EDA stress detection
DeependraVerma/AI-Lecture-Transcriber-YouTube-to-Notes-Converter
Effortlessly convert YouTube lectures to concise notes with our AI transcriber. Streamline learning and comprehension with just a click!
Edouard99/Stress_Detection_ECG
:stethoscope: This project aims to detect stress state based on Electrocardiogram :hearts: signals (WESAD Dataset) analysis with a deep learning model.
BradySheehan/wesad_experiments
Experimenting with WESAD using neural networks.
SteliosTsop/QF-image-segmentation-keras
In this repository, we present an Semantic Segmentation code, based on U-net architecture, that is used for the topographic characterization of the fracture surfaces of brittle materials. The results of this work are presented in the publication: " Toward quantitative fractography using convolutional neural networks ".
berdakh/mne_workshop_amsterdam
Materials for workshops on the open neural time series analysis toolbox MNE-Python
berdakh/source-Imaging
Collection of codes created for EEG source imaging using MNE python
xalentis/Stress
Ensemble Machine Learning Model Trained on Combined Public Datasets Generalizes Well for Stress Prediction Using Wearable Device Biomarkers