chesnokov-yuriy

chesnokov-yuriy's Stars

• yandexdataschool/nlp_course

  YSDA course in Natural Language Processing

  Language:Jupyter Notebook9.7k366462.6k

• udlbook/udlbook

  Understanding Deep Learning - Simon J.D. Prince

  Language:Jupyter Notebook6.1k911781.3k

• geopy/geopy

  Geocoding library for Python.

  Language:Python4.4k89281644

• osm-search/Nominatim

  Open Source search based on OpenStreetMap data

  Language:Python3.1k942k712

• PacktPublishing/Deep-Reinforcement-Learning-Hands-On

  Hands-on Deep Reinforcement Learning, published by Packt

  Language:Python2.8k120811.3k

• rdkit/rdkit

  The official sources for the RDKit library

  Language:HTML2.6k823.3k869

• orico/www.mlcompendium.com

  The Machine Learning & Deep Learning Compendium was a list of references in my private & single document, which I curated in order to expand my knowledge, it is now an open knowledge-sharing project compiled using Gitbook.

  2.1k390225

• PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition

  Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

  Language:Jupyter Notebook1.9k10601k

• thampiman/reverse-geocoder

  A fast, offline reverse geocoder in Python

  Language:Python1.9k3649160

• PacktPublishing/Node.js-Design-Patterns-Third-Edition

  Node.js Design Patterns Third Edition, published by Packt

  Language:JavaScript1.6k5316475

• hfawaz/dl-4-tsc

  Deep Learning for Time Series Classification

  Language:Python1.5k4847569

• PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading

  Hands-On Machine Learning for Algorithmic Trading, published by Packt

  Language:Jupyter Notebook1.4k7612629

• PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original

  Machine Learning for Algorithmic Trading, Second Edition - published by Packt

  Language:Jupyter Notebook1.2k6916472

• PacktPublishing/Deep-Learning-with-Keras

  Code repository for Deep Learning with Keras published by Packt

  Language:Jupyter Notebook1.1k10413716

• intel/openvino-plugins-ai-audacity

  A set of AI-enabled effects, generators, and analyzers for Audacity®.

  Language:C++8992424057

• alexminnaar/time-series-classification-and-clustering

  Time series classification and clustering code written in Python.

  Language:Jupyter Notebook778428340

• pycountry/pycountry

  A Python library to access ISO country, subdivision, language, currency and script definitions and their translations.

  Language:Python74313138123

• hfawaz/InceptionTime

  InceptionTime: Finding AlexNet for Time Series Classification

  Language:Python6322225146

• sccn/eeglab

  EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD

  Language:MATLAB59226717241

• mims-harvard/UniTS

  A unified multi-task time series model.

  Language:Python409143053

• pulseaudio-equalizer-ladspa/equalizer

  Pulseaudio LADSPA Equalizer

  Language:Shell13855115

• PacktPublishing/Interpretable-Machine-Learning-with-Python-2E

  Interpretable ML with Python, 2E - published by Packt

  Language:Jupyter Notebook772734

• damianbraun/nominatim

  OSM Nominatim API module

  Language:Python275510

• johnschwenck/bp

  An R package for analyzing blood pressure data

  Language:R24495

• SMU-MedicalVision/ECG-MoCo-Classfication

  Practical cardiac events intelligent diagnostic algorithm for wearable 12-lead ECG via self-supervised learning on large-scale dataset

  Language:Python186

• orico/www.opscompendium.com

  The Ops Compendium is a resource list for dataops, mlops, devops, etc, which I'm actively curating in order to expand my knowledge, it is now an open knowledge-sharing project compiled using Gitbook.

  6101

• pymche/Machine-Learning-Obesity-Classification

  Classification on levels of obesity - data cleaning, exploratory analysis, preprocessing with pipeline, model selection and classification report.

  Language:Jupyter Notebook6106

• SMU-MedicalVision/MESEL

  Code for paper "Multi-expert ensemble ECG diagnostic algorithm using mutually exclusive-symbiotic correlation between 254 hierarchical multiple labels".

  Language:Python50

• santosomar/epss-client

  a Python client to query the FIRST EPSS API

  Language:Python430

• jaketuricchi/BodyWeight_Imputation_Validation_Variability

  Script associated with the publication: https://mhealth.jmir.org/preprint/17977. It describes how to deal with missing data, and the impact of missingness on linear and non-linear calculation of body weight variability, which may be an important marker in health epidemiology.

  Language:R21