GitPlanet

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details
All Projects → bokeh → Bokeh Notebooks

bokeh / Bokeh Notebooks

Licence: bsd-3-clause
Interactive Web Plotting with Bokeh in IPython notebook

Labels

jupyter-notebook

Projects that are alternatives of or similar to Bokeh Notebooks

Jetracer
An autonomous AI racecar using NVIDIA Jetson Nano
Stars: ✭ 616 (-2.07%)
Mutual labels:  jupyter-notebook
Tutorials
A series of machine learning tutorials for Torch7
Stars: ✭ 621 (-1.27%)
Mutual labels:  jupyter-notebook
Anchor
Code for "High-Precision Model-Agnostic Explanations" paper
Stars: ✭ 629 (+0%)
Mutual labels:  jupyter-notebook
Swift Models
Models and examples built with Swift for TensorFlow
Stars: ✭ 619 (-1.59%)
Mutual labels:  jupyter-notebook
Ebookmlcb
ebook Machine Learning cơ bản
Stars: ✭ 619 (-1.59%)
Mutual labels:  jupyter-notebook
Cvnd exercises
Exercise notebooks for CVND.
Stars: ✭ 622 (-1.11%)
Mutual labels:  jupyter-notebook
Introduction to ml with python
Notebooks and code for the book "Introduction to Machine Learning with Python"
Stars: ✭ 5,843 (+828.93%)
Mutual labels:  jupyter-notebook
Toolkitten
A toolkit for #1millionwomentotech community.
Stars: ✭ 630 (+0.16%)
Mutual labels:  jupyter-notebook
Mina
Mina is a new cryptocurrency with a constant size blockchain, improving scaling while maintaining decentralization and security.
Stars: ✭ 617 (-1.91%)
Mutual labels:  jupyter-notebook
Tensorflow Workshop
This repo contains materials for use in a TensorFlow workshop.
Stars: ✭ 628 (-0.16%)
Mutual labels:  jupyter-notebook
Deeplearning Assignment
深度学习笔记
Stars: ✭ 619 (-1.59%)
Mutual labels:  jupyter-notebook
Kalman
Some Python Implementations of the Kalman Filter
Stars: ✭ 619 (-1.59%)
Mutual labels:  jupyter-notebook
David Silver Reinforcement Learning
Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.
Stars: ✭ 623 (-0.95%)
Mutual labels:  jupyter-notebook
Machine Learning Book
《机器学习宝典》包含：谷歌机器学习速成课程（招式）+机器学习术语表（口诀）+机器学习规则（心得）+机器学习中的常识性问题 （内功）。该资源适用于机器学习、深度学习研究人员和爱好者参考！
Stars: ✭ 616 (-2.07%)
Mutual labels:  jupyter-notebook
Mxnet Notebooks
Notebooks for MXNet
Stars: ✭ 629 (+0%)
Mutual labels:  jupyter-notebook
Breast cancer classifier
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Stars: ✭ 614 (-2.38%)
Mutual labels:  jupyter-notebook
Bamboolib
bamboolib - a GUI for pandas DataFrames
Stars: ✭ 622 (-1.11%)
Mutual labels:  jupyter-notebook
Falcon
Brushing and linking for big data
Stars: ✭ 627 (-0.32%)
Mutual labels:  jupyter-notebook
Fastai2
Temporary home for fastai v2 while it's being developed
Stars: ✭ 630 (+0.16%)
Mutual labels:  jupyter-notebook
Kmcuda
Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA
Stars: ✭ 627 (-0.32%)
Mutual labels:  jupyter-notebook
View All Similar Projects ➔

Bokeh in Jupyter Notebooks

Welcome to Bokeh in Jupyter Notebooks!

Bokeh is a Python interactive visualization library for large datasets that natively uses the latest web technologies. Its goal is to provide elegant, concise construction of novel graphics in the style of Protovis/D3, while delivering high-performance interactivity over large data to thin clients.

These Jupyter notebooks provide useful Bokeh examples and a tutorial to get started. You can download the repository and execute jupyter notebook from your terminal to try out the notebooks locally on your own machine.

Alternatively, you can immediately launch live versions of the Tutorial notebooks in your browser on mybinder.org.

Please visit the Bokeh web page for more information and full documentation, and the Bokeh Discourse for community discussion.

Be sure to follow us on Twitter @bokeh!

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].