zeydabadi

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

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.

zeydabadi/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.

zeydabadi/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.

zeydabadi/ABBA

A symbolic time series representation building Brownian bridges

zeydabadi/attn2d

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

zeydabadi/awesome-datascience

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

zeydabadi/aws-machine-learning-university-accelerated-cv

Machine Learning University: Accelerated Computer Vision Class

zeydabadi/aws-machine-learning-university-accelerated-nlp

Machine Learning University: Accelerated Natural Language Processing Class

zeydabadi/aws-machine-learning-university-accelerated-tab

Machine Learning University: Accelerated Tabular Data Class

zeydabadi/Colab-Hacks

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

zeydabadi/deep-learning-notes

Experiments with Deep Learning

zeydabadi/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.

zeydabadi/examples

TensorFlow examples

zeydabadi/ganhacks

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

zeydabadi/generative-ai-for-beginners

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

zeydabadi/icebeem

Code for ICE-BeeM paper - NeurIPS 2020

zeydabadi/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.

zeydabadi/keras-tuner

Hyperparameter tuning for humans

zeydabadi/learn-python

📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.

zeydabadi/learn-python3

Jupyter notebooks for teaching/learning Python 3

zeydabadi/mathematics-roadmap

A Comprehensive Roadmap to Mathematics

zeydabadi/MEDIUM_NoteBook

Repository containing notebooks of my posts on Medium

zeydabadi/mit-15-003-data-science-tools

Study guides for MIT's 15.003 Data Science Tools

zeydabadi/MuseProject

This repository consists of codes that can be used to preprocess data from Muse headband and apply ML models to it to classify data on basis of colours RGB

zeydabadi/PU-OC

This repository accompanies the paper "Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled Data".

zeydabadi/Python

All Algorithms implemented in Python

zeydabadi/pytorch-ts

Tutorials on using encoder decoder architecture for time series forecasting

zeydabadi/Resources-For-CS-Students

A list of resources such as scholarships, fellowships, and mailing list for helping CS students succeed in their career

zeydabadi/SecretScanner

Find secrets and passwords in container images and file systems

zeydabadi/shap-hypetune

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

zeydabadi/starter-hugo-academic