Pinned Repositories
AWESOME-FER
🔆 Top conferences & Journals focused on Facial expression recognition (FER)/ Facial action unit (FAU) 💫 ✨
AWESOME-MER
🔆 📝 A reading list focused on Multimodal Emotion Recognition (MER) 👂👄 👀 💬
awesome-network-analysis
A curated list of awesome network analysis resources.
axcell
Tools for extracting tables and results from Machine Learning papers
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
FirstCourseNetworkScience
Tutorials, datasets, and other material associated with textbook "A First Course in Network Science" by Menczer, Fortunato & Davis
Mathematics-of-Epidemics-on-Networks
Source code accompanying 'Mathematics of Epidemics on Networks' by Kiss, Miller, and Simon http://www.springer.com/us/book/9783319508047 . Documentation for the software package is at https://epidemicsonnetworks.readthedocs.io/en/latest/
networkx-tutorial
Twitter Network Analysis with NetworkX
python-machine-learning-book-3rd-edition
The "Python Machine Learning (3rd edition)" book code repository
stat453-deep-learning-ss20
STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)
rajeshkpandey's Repositories
rajeshkpandey/AWESOME-FER
🔆 Top conferences & Journals focused on Facial expression recognition (FER)/ Facial action unit (FAU) 💫 ✨
rajeshkpandey/awesome-network-analysis
A curated list of awesome network analysis resources.
rajeshkpandey/FirstCourseNetworkScience
Tutorials, datasets, and other material associated with textbook "A First Course in Network Science" by Menczer, Fortunato & Davis
rajeshkpandey/Mathematics-of-Epidemics-on-Networks
Source code accompanying 'Mathematics of Epidemics on Networks' by Kiss, Miller, and Simon http://www.springer.com/us/book/9783319508047 . Documentation for the software package is at https://epidemicsonnetworks.readthedocs.io/en/latest/
rajeshkpandey/networkx-tutorial
Twitter Network Analysis with NetworkX
rajeshkpandey/python-machine-learning-book-3rd-edition
The "Python Machine Learning (3rd edition)" book code repository
rajeshkpandey/stat453-deep-learning-ss20
STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)
rajeshkpandey/AWESOME-MER
🔆 📝 A reading list focused on Multimodal Emotion Recognition (MER) 👂👄 👀 💬
rajeshkpandey/axcell
Tools for extracting tables and results from Machine Learning papers
rajeshkpandey/data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
rajeshkpandey/deeplearning-models
A collection of various deep learning architectures, models, and tips
rajeshkpandey/digit_recognizer
CNN digit recognizer implemented in Keras Notebook, Kaggle/MNIST (0.995).
rajeshkpandey/Facial-Expression-Recognition.Pytorch
A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset
rajeshkpandey/GNNPapers
Must-read papers on graph neural networks (GNN)
rajeshkpandey/html-css-javascript
Full Stack Development(HTML,CSS and Javascript)
rajeshkpandey/JavaDSA
rajeshkpandey/Kaggle-Play
:seedling: Playing in Kaggle Playground
rajeshkpandey/mlbook
rajeshkpandey/Network-Science-Lectures
Network Science, Complex Networks
rajeshkpandey/networkepidemics
Research work on Network Epidemics
rajeshkpandey/paperswithcode-data
The full dataset behind paperswithcode.com
rajeshkpandey/rajeshkpandey.github.io
Personal Webpage
rajeshkpandey/releasing-research-code
Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)
rajeshkpandey/sota-extractor
The SOTA extractor pipeline
rajeshkpandey/sotabench-api
Easily benchmark Machine Learning models on selected tasks and datasets
rajeshkpandey/sotabench-eval
Easily evaluate machine learning models on public benchmarks
rajeshkpandey/Spring-boot-swagger-config
Spring boot swagger basic integration
rajeshkpandey/stat479-machine-learning-fs19
Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison
rajeshkpandey/torchbench
Easily benchmark machine learning models in PyTorch
rajeshkpandey/Vitis-Tutorials