zeydabadi Goto Github PK

30-days-of-python

30 days of Python programming challenge is a step by step guide to learn the Python programming language in 30 days. This challenge may take up to 100 days, follow your own pace.

abba

A symbolic time series representation building Brownian bridges

aima-glossary

attn2d

Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

aws-machine-learning-university-accelerated-cv

Machine Learning University: Accelerated Computer Vision Class

aws-machine-learning-university-accelerated-nlp

Machine Learning University: Accelerated Natural Language Processing Class

aws-machine-learning-university-accelerated-tab

Machine Learning University: Accelerated Tabular Data Class

bash_scripts

Bash scripts that I wrote for my work at MAC

bayesianprobabilitiesworkshop

A collection of questions and solutions to problems presented at Rasmus Bååth's Bayesian probabilities workshop.

biosignalsnotebooks

biosignalsnotebooks project includes a set of Jupyter Notebooks explaining some processing tasks which have been specially designed for biosignalsplux and OpenSignals users. A Python package is also present, containing some functions to support biosignalsnotebooks notebooks or to be used independently.

bmi500

capsnet-tensorflow

A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules

cnn-registration

A image registration method using convolutional neural network features.

code_similarity

colab-hacks

Simple Hacks for Google Colaboratory to boost your productivity and help you to perform daily tasks.

comaprison_of_anomaly_detection_algorithms

Compares various Anomaly detection algorithms on basis of AUC-ROC score and AP scores

de-id

Perl and Python code for de-identifying electronic medical records

deep-learning-notes

Experiments with Deep Learning

deeplearning-models

A collection of various deep learning architectures, models, and tips

deeptcn

differential_privacy

dl-visuals

Over 200 figures and diagrams of the most popular deep learning architectures and layers FREE TO USE in your blog posts, slides, presentations, or papers.

examples

TensorFlow examples

ganhacks

starter from "How to Train a GAN?" at NIPS2016

generative-ai-for-beginners

12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

gif_your_nifti

How to create fancy GIFs from an MRI brain image

icebeem

Code for ICE-BeeM paper - NeurIPS 2020

istn

Image-and-Spatial Transformer Networks

kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.