Anaconda Libraries

9 Components & Libraries

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Anaconda Libraries

Visual analysis and diagnostic tools to facilitate machine learning model selection.

Yellowbrick is compatible with Python 3.4 or later and also depends on scikit-learn and matplotlib. The simplest way to install Yellowbrick and its dependencies is from PyPI with pip, Python's prefer…

🛠 All-in-one web-based IDE specialized for machine learning and data science.

The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on you…

Anaconda turns your Sublime Text 3 in a full featured Python development IDE including autocompletion, code linting, IDE features, autopep8 formating, McCabe complexity checker Vagrant and Docker support for Sublime Text 3 using Jedi, PyFlakes, pep8, MyPy, PyLint, pep257 and McCabe that will never freeze your Sublime Text 3

The plugins ecosystem in Sublime Text have improved by a lot in the past few years, there are many alternatives to anaconda that might work better for you Anaconda works out of the box but there are …

대학 강의를 위한 강의자료 및 소스코드 저장소 Python Lecture slide & code for University Student.

2016년 겨울방학 중앙대학교 Python 기초과목 구글 파이썬 스타일 가이드로 시작하는 프로그래밍 Ver 1.1.1 (Last Update 2018-06-14) 본 Repository는 GPL-3.0 라이센스를 따릅니다. 상업적, 교육용, 개인적인 사용이 가능합니다. 자세한 라이센스 제약사항은 본 글 하단을 참조하세요. 강의 슬라이드는 복습 =&g…

The smallest Docker image with Miniconda3 (Python 3.7) (~143MB)

Download size of this image is only: Once you have run this command you will get printed 'Hello World' from Python!

A conda environment and docker container to support using earth and environmental data in Python.

The tutorial above will provide you with more detailed setup instructions. But here are the cliff notes: To begin, install the environment using: This will take a bit of time to run. You can update y…

A python project starter template for data-analytics and data-science.

A project template to quick start data analytics and machine learning task. You can connect with me here:

🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.

Using Anaconda is a GREAT way to keep everything consistentregardless of what machine you run your code on. The following command will create an Anaconda virtual environment with themodules listed in…