naivoder
Machine learning engineer and PhD student, interested in computer vision, reinforcement learning, meta-learning, and knowledge representation.
R-DEX SystemsAtlanta, Georgia
naivoder's Stars
SICC-Group/GMAH
subGoal-based Multi-Agent Hierarchical reinforcement learning method
SakanaAI/AI-Scientist
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
dair-ai/ML-Papers-of-the-Week
🔥Highlighting the top ML papers every week.
Allenpandas/Reinforcement-Learning-Papers
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL),including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
naterini/docker-scale-out
Slurm cluster in a docker-compose for training
ultimate-pms/ultimate-media-server-core
A bunch of scripts that I've collected, written, and forked for the ultimate administration & automation of your Media Server - Think of this as your "Media server in a box"
Intelligent-Microsystems-Lab/Network_Analysis
Pytorch code to view the effectiveness of a neural network over time using the Henze-Penrose statistic and Fisher permutation test for means.
bethgelab/foolbox
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
jonasrauber/foolbox-tensorflow-keras-applications
The pretrained TensorFlow Keras models with a Foolbox Zoo compatible interface
Rishit-dagli/Gradient-Centralization-TensorFlow
Instantly improve your training performance of TensorFlow models with just 2 lines of code!
the-full-stack/website
Source for https://fullstackdeeplearning.com
chasehamrick/Turn-Picture-into-Art
Project for Computer Photography that takes in an image / photo and outputs it altered to look like a painting / cartoon.
MarcoForte/bayesian-matting
Python implementation of Bayesian Matting from Yung-Yu Chuang, Brian Curless, David H. Salesin, and Richard Szeliski. A Bayesian Approach to Digital Matting. In Proceedings of IEEE Computer Vision and Pattern Recognition (CVPR 2001), Vol. II, 264-271, December 2001
jbhuang0604/awesome-computer-vision
A curated list of awesome computer vision resources
amirziai/sklearnflask
Flask API for training and predicting using scikit learn models
jakevdp/sklearn_tutorial
Materials for my scikit-learn tutorial
TheAlgorithms/C
Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.
ahmedfgad/NumPyCNN
Building Convolutional Neural Networks From Scratch using NumPy
chaoming0625/NumpyDL
Deep Learning Library. For education. Based on pure Numpy. Support CNN, RNN, LSTM, GRU etc.
rougier/from-python-to-numpy
An open-access book on numpy vectorization techniques, Nicolas P. Rougier, 2017
ddbourgin/numpy-ml
Machine learning, in numpy
Kyubyong/numpy_exercises
Numpy exercises.
rougier/numpy-100
100 numpy exercises (with solutions)
theAIGuysCode/tensorflow-yolov4-tflite
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
rchavezj/OpenCV_Projects
List of OpenCV projects to further increase the computer vision community. Coding in Python & C++(In progress).
huggingface/datasets
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
google/sentencepiece
Unsupervised text tokenizer for Neural Network-based text generation.
niderhoff/nlp-datasets
Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)
karan/Projects
:page_with_curl: A list of practical projects that anyone can solve in any programming language.
fchollet/keras-resources
Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library