Displaying 1 to 20 from 170 results

jupyter-vim-binding - Jupyter meets Vim. Vimmer will fall in love.

  •    Javascript

Do you use Vim? And you need to use Jupyter Notebook? This is a Jupyter Notebook (formerly known as IPython Notebook) extension to enable Vim like environment powered by CodeMirror's Vim. I'm sure that this plugin helps to improve your QOL. While I changed my job, I don't use jupyter notebook and I can't make enough time to maintain this plugin.

lucid - A collection of infrastructure and tools for research in neural network interpretability.

  •    Jupyter

Lucid is a collection of infrastructure and tools for research in neural network interpretability. In particular, it provides state of the art implementations of feature visualization techniques, and flexible abstractions that make it very easy to explore new research directions.

handson-ml - A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow

  •    Jupyter

First, you will need to install git, if you don't have it already. If you want to go through chapter 16 on Reinforcement Learning, you will need to install OpenAI gym and its dependencies for Atari simulations.

PythonDataScienceHandbook - Python Data Science Handbook: full text in Jupyter Notebooks

  •    Jupyter

This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks. Run the code using the Jupyter notebooks available in this repository's notebooks directory.




CADL - Course materials/Homework materials for the FREE MOOC course on "Creative Applications of Deep Learning w/ Tensorflow" #CADL

  •    Jupyter

This repository contains lecture transcripts and homework assignments as Jupyter Notebooks for the first of three Kadenze Academy courses on Creative Applications of Deep Learning w/ Tensorflow. It also contains a python package containing all the code developed during all three courses. The first course makes heavy usage of Jupyter Notebook. This will be necessary for submitting the homeworks and interacting with the guided session notebooks I will provide for each assignment. Follow along this guide and we'll see how to obtain all of the necessary libraries that we'll be using. By the end of this, you'll have installed Jupyter Notebook, NumPy, SciPy, and Matplotlib. While many of these libraries aren't necessary for performing the Deep Learning which we'll get to in later lectures, they are incredibly useful for manipulating data on your computer, preparing data for learning, and exploring results.

dive-into-machine-learning - Dive into Machine Learning with Python Jupyter notebook and scikit-learn!

  •    

I learned Python by hacking first, and getting serious later. I wanted to do this with Machine Learning. If this is your style, join me in getting a bit ahead of yourself. I suggest you get your feet wet ASAP. You'll boost your confidence.

distiller - Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research

  •    Python

Distiller is an open-source Python package for neural network compression research. Network compression can reduce the memory footprint of a neural network, increase its inference speed and save energy. Distiller provides a PyTorch environment for prototyping and analyzing compression algorithms, such as sparsity-inducing methods and low-precision arithmetic.

dashboards - Jupyter Dashboards Layout Extension

  •    Jupyter

The dashboards layout extension is an add-on for Jupyter Notebook. It lets you arrange your notebook outputs (text, plots, widgets, ...) in grid- or report-like layouts. It saves information about your layouts in your notebook document. Other people with the extension can open your notebook and view your layouts. For a sample of what's possible with the dashboard layout extension, have a look at the demo dashboard-notebooks in this repository.


nbdime - Tools for diffing and merging of Jupyter notebooks.

  •    Python

nbdime provides tools for diffing and merging of Jupyter Notebooks. See the installation docs for more installation details and development installation instructions.

scikit-learn-videos - Jupyter notebooks from the scikit-learn video series

  •    Jupyter

This video series will teach you how to solve machine learning problems using Python's popular scikit-learn library. It was featured on Kaggle's blog in 2015. There are 9 video tutorials totaling 4 hours, each with a corresponding Jupyter notebook. The notebook contains everything you see in the video: code, output, images, and comments.

deepschool.io - Deep Learning tutorials in jupyter notebooks.

  •    Jupyter

See here for installing on windows. 1: Refer to this Dockerfile and this for information on how the docker image was built.

lectures-labs - Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay

  •    Jupyter

The course covers the basics of Deep Learning, with a focus on applications. Note: press "P" to display the presenter's notes that include some comments and additional references.

jupyter-scala - Lightweight Scala kernel for Jupyter / IPython 3

  •    Scala

Jupyter Scala is a Scala kernel for Jupyter. It aims at being a versatile and easily extensible alternative to other Scala kernels or notebook UIs, building on both Jupyter and Ammonite. The current version is available for Scala 2.11. Support for Scala 2.10 could be added back, and 2.12 should be supported soon (via ammonium / Ammonite).

machine-learning - :earth_americas: machine learning algorithms tutorials (mainly in Python3)

  •    HTML

This is a continuously updated repository that documents personal journey on learning data science, machine learning related topics. Forecasting methods for timeseries-based data.

jupyter-themes - Custom Jupyter Notebook Themes

  •    CSS

While I love my job as a researcher, it doesn't exactly bring home the bacon. I mean.. it brings home some bacon... but like... not enough bacon? Right. Anyway, a colleague suggested I add an optional donation badge so users can help support projects like jupyter-themes (and the forthcoming lab-themes which will give users similar control over the look and feel of Jupyter Lab. Currently in early stages of development). I firmly believe that software is best served open and, as such, am committed to providing free and easy access to all my code. So if you can't make a financial contribution, then don't and pip install it anyway! But if you're sitting on some extra cash and enjoy using a package I've developed, then any amount helps and I greatly appreciate it.

pipeline - PipelineAI: Real-Time Enterprise AI Platform

  •    HTML

Each model is built into a separate Docker image with the appropriate Python, C++, and Java/Scala Runtime Libraries for training or prediction. Use the same Docker Image from Local Laptop to Production to avoid dependency surprises.