jupyter_console | conda | Package Usage

taduyde/kite-python-blog-post-code

6.0.0 Practical Machine Learning with Python and Keras/environment.yml

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stevenrouk/evolution-of-machine-learning

Using natural language processing techniques such as topic modeling to analyze the evolution of machine learning as a field, using ArXiv research paper descriptions as the dataset.

6.0.0 environment.yml

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MartaFerrerC/Robotics

6.0.0 environment.yml

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analyticalmonk/foobar

6.0.0 simple_workflow/environment.yaml

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pavelexpertov/scales-ml

6.1.0 environment.yml

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CamHolman/cell_counting

Tools to automatically count signal-positive cells from confocal IHC images

6.0.0 environment.yml

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KC2016/ds-ml-ai-challenge

Challenge Codedoor

5.2.0 environment.yml

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diogomatoschaves/berlin-house-prices-analysis

6.1.0 environment.yaml

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eunicode/ml-ds-covid

Predict the risk of Covid-19 fatality based on epidemiological parameters using machine learning and data science.

6.1.0 zdump/environment.yml

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Fernando23296/dluda

Repository for notes of Udacity's Deep Learning Nanodegree

6.1.0 environment.yaml

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OfirKedem/Fourier4Dummies

basic intro to Fourier analysis in python

6.1.0 environment.yml

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maliksalam/powerful_python

Work and Notes from Powerful Python by Aaron Maxwell

6.1.0 environment.yml

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shalevy1/kite-python-blog-post-code Fork of kiteco/kite-python-blog-post-code

Code snippets from Kite blog posts

6.0.0 Practical Machine Learning with Python and Keras/environment.yml

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zb46392/poker

6.4.0 environment.yaml

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walkingCommiter/css_political_ads

Political Adverts Analyzer

6.0.0.* environment.yml

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nsankabathula/en-nlp

5.2.0 environment.yml

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bumblebealu/draft_website

6.4.3 environment.yml

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YunluZhu/SAMPL-analysis-v5-lab

arrange, analyze, and plot data from free swimming apparatus

6.4.3 environment.yml

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FORCOLAB-UofT/INFOX

This is a prototype for overview of GitHub forks.

5.2.0 environment.yaml

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nixiwang/PISAnalysisTool

An analysis tool of multi-level modeling for PISA dataset

6.0.0 environment.yml

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amanpreetsingh459/deep-learning_first-neural-network

5.0.0 environment.yaml

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PattanaikL/GeoMol

6.4.0 devtools/environment.yml

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legiov/ml

6.4.0 project 0/environment.yaml

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micvolk/Buy-and-Rent-Price-Estimator-for-Apartments

Built a machine learning model based on scraped immowelt.de data that estimates apartment prices for buy & rent in german federal state North Rhine-Westphalia.

6.4.0 environment.yml

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emma-data-works/ds-class-intro

6.4.0 python_basics/class01/environment.yml

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ramg93/Pythonic-Email-Sender

6.4.3 environment.yml

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dsbrown1331/CoRL2019-DREX

Code and project page for D-REX algorithm from the paper "Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations" presented at CoRL 2019.

5.2.0 drex-atari/baselines/baselines/common/environment.yaml

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Jaureguy760/atac_ml_project

6.4.3 env/environment.yml

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bioFAM/slalom

5.0.0 doc/environment.yml

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PmagPy/PmagPy

Python-based tools for paleomagnetic research

5.2.0 environment.yml

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jonnyhtw/weather-types

6.4.0 environment.yml

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gw-odw/odw-2022

Tutorials for GW Open Data Workshop, 2022

6.4.0 environment.yml

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DamienIrving/ocean-analysis

Code used for analysis and visualiation of ocean model data during my postdoc

6.3.0 environment.yml

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emma-oc/ds-class-intro

6.1.0 python_basics/class01/environment.yml

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avstack-lab/lib-avstack-api

Unlocking consistent interfacing to the most useful autonomous vehicle datasets and simulators.

==6.4.4 environment.yml

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jimmy-nguyen-data-science/Travel-Insurance-Predictions

Machine learning project using Python on travel insurance predictions for flights before the COVID-19 pandemic

6.4.0 environment.yml

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UCL-DSS/fundamental-python-workshop

Fundamental Python workshop, proudly presented by the UCL Data Science Society

6.4.0 environment.yml

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WhoIsJack/hackday-pybioimage

Repo for UCL Festival of Code Hackday python group working on modernizing and extending the python bioimage analysis tutorial.

6.4.0 environment.yml

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kit-cel/lecture-examples

Sample scripts used in the lectures of the CEL (Communications Engineering Lab) at KIT

6.0.0.* ccgbc/environment.yml

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RobinPelkner/ProjectUniBo

6.4.3 environment.yml

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adenger/subpred3

Code for the manuscript "Optimized data set and feature construction for substrate prediction of membrane transporters"

6.4.3 environment.yml

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kiteco/kite-python-blog-post-code

Code snippets from Kite blog posts

6.0.0 Practical Machine Learning with Python and Keras/environment.yml

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Germoe/sb_intermediate_course

This repository contains all the notes and submissions for the Intermediate Data Science: Python Course

6.0.0 environment.yml

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loic001/deep_bci_study

Code for paper "Simple deep neural networks show state-of-the-art performance in ERP-based BCI"

5.2.0 environment.yml

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three-musketeers-team-04/Portfolio_Optimization

6.0.0 code/requirements/environment.yaml

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CNES/swot-hydrology-toolbox

6.0.0 environment.yml

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victorbonnet/waldo_finder_app

Mobile apps to detect Waldo using a artificial neural network.

5.2.0 environment.yml

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SheepInMeadow/ELISA-APP

A tool for processing ELISA Reader output, developed for the Rheumatology department at Leiden University Medical Centre.

6.4.0 ELISA_app/environment.yml

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Geffen-Cooper/continual_learning_playground

6.4.3 environment.yml

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SR-MEiTY/i-SpeakR

Speaker recognition toolkit for Indian languages

6.4.0 environment.yml

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semasuka/Credit-card-approval-prediction-classification

Credit risk analysis for credit card applicants

6.4.0 assets/environment.yml

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RK-MSU/CSCI-347-Data-Mining

CSCI-347 Data Mining Spring 2022 @ Montana State University

6.4.3 environment.yml

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evinjaff/speedrunsunchained

Django & Node.js app of my speedrun game idea

6.4.3 data/environment.yml

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DatenkrakeWasTaken/twitter_bot_popularity_evaluation

6.4.0 .github/workflows/environment.yml

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NoahPichl/MLPC_The_haunted_turtles

6.4.3 environment.yml

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goparajug/DeepLearnig

https://github.com/tommytracey/udacity.git

5.1.0 environment.yml

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mtl-brainhack-school-2019/ecg_pupillometry_pipeline_kaufmann

Brain Hack School 2019 Project

6.0.0 environment.yml

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bhasarma/mlcoursezoom-camp

This repository contains notebooks, homework, projects and notes done during Machine Learning Zoomcamp course.

6.4.3 WK08-09-midterm-project/environment.yml

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ZIB-IOL/avi_at_scale

Code for the paper: [Wirth, E., Kera, H., and Pokutta, S. (2022). Approximate vanishing ideal computations at scale.](https://arxiv.org/abs/2207.01236)

6.4.0 environment.yml

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elwirth/avi_at_scale

Code for the paper: [Wirth, E., Kera, H., and Pokutta, S. (2022). Approximate vanishing ideal computations at scale.](https://arxiv.org/abs/2207.01236)

6.4.0 environment.yml

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christophernhill/prov-profiles

Provisioning profiles

6.4.0.* ronin/ubuntu20/2022a/environment.yml
6.4.0.* ronin/ubuntu20/all-in-one/environment.yml

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Britefury/cutmix-semisup-seg

Semi-supervised semantic segmentation needs strong, varied perturbations

6.1.0 environment.yml

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oskarfernlund/orthogonal-SVGP

Orthogonal sparse variational Gaussian processes (SVGP's) in TensorFlow.

6.4.4 env/environment.yml

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zhdanovkm/data_science_study

first steps in DS

6.4.0 project 0/environment.yaml
6.4.0 project 1/environment.yaml

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villegar/xxii-simmac

XXII SIMMAC (International Symposium on Mathematical Methods Applied to Sciences) - University of Costa Rica

6.1.0.* environment.yml

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Sette/fifa_dataset 📦

6.0.0 environment.yml

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xiaohan2012/signed-local-community

Code for paper "Searching for polarization in signed graphs: a local spectral approach" (published at WebConf 2020)

5.2.0 environment.yml

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pnnl/deps_arXiv2020

Differentiable predictive control (DPC) policy optimization examples.

6.0.0 environment.yml

Size: 18.8 MB - Last synced: 8 months ago - Pushed: 8 months ago

tne-lab/flexibility-pybehave Fork of tne-lab/py-behav-box-v2

6.4.0 environment.yml

Size: 473 KB - Last synced: 12 months ago - Pushed: 12 months ago

YufengLuo98/CMPT-459-Course-Project

6.4.0 environment.yml

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mrejmon/black-and-white-movies

5.2.0 environment.yml

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markovmodel/msmrd2

6.1.0 environment.yml

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ScientificCodingKids/VEX_47114A_tutorials

Teaching materials for robotics, math, physics, AI and more

6.4.3 environment.yml

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John-Kim93/3MinutesFor1Minute

second project in SSAFY

6.4.0 BE/api/environment.yaml

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petermckeeverPerform/themepy

An open source theme selector for matplotlib

6.1.0.* environment.yml

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xchem/acellera-tools

Tools developed by acellera for Fragalysis

6.0.0 apps/MDSimulator/environment.yml
6.0.0 apps/SystemBuilder/environment.yml

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richardso21/SERP2021-BGSUB

SERP Project Submission for the Terra NYC STEM Fair 2021: Caribou detection and automated annotation from image data captured in the Alaskan Wilderness.

6.1.0 environment.yml

Size: 230 MB - Last synced: about 1 year ago - Pushed: over 2 years ago

k-papadakis/geospatial-labs

Remote Sensing on Satellite Imagery and Videos with Deep Learning

6.4.4 environment.yml

Size: 307 MB - Last synced: 3 months ago - Pushed: over 1 year ago

elwirth/open_loop_fw

Code for the paper: Wirth, E., Kerdreux, T., and Pokutta, S. (2022). Acceleration of Frank-Wolfe algorithms with open loop step-sizes.

6.4.0 environment.yml

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mbillingr/coronadata

Plots based on AGES' corona incidence data

6.2.0 environment.yml

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JayMaier/SewAligned

6.2.0 environment.yml

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Mert18/data-analysis-vg-ivysaur 📦

6.2.0 environment.yml

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howen7/Predictive_Modeling

6.1.0 environment.yml

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Experiment outputs are now available from the Coupled Model Intercomparison Project's 6th phase (CMIP6) and the past climate experiments defined in the Model Intercomparison Project's 4th phase (PMIP4). All of this output is freely available from the Earth System Grid Federation (ESGF). Yet there are overheads in analysing this resource that may prove complicated or prohibitive. Here we document the steps taken by ourselves to produce ensemble analyses covering past and future simulations. We outline the strategy used to curate, adjust the monthly calendar aggregation and process the information downloaded from the ESGF. The results of these steps were used to perform analysis for several of the initial publications arising from PMIP4. We provide post-processed fields for each simulation, such as climatologies and common measures of variability. Example scripts used to visualise and analyse these fields is provided for several important case studies.