data-science-ipython-notebooks | Data science Python notebooks : Deep learning

by donnemartin Python Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | data-science-ipython-notebooks Summary

data-science-ipython-notebooks is a Python library typically used in Institutions, Learning, Education, Big Data, Deep Learning, Tensorflow, Numpy, Spark, Hadoop applications. data-science-ipython-notebooks has no bugs, it has no vulnerabilities and it has medium support. However data-science-ipython-notebooks build file is not available and it has a Non-SPDX License. You can download it from GitHub.

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

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Quality

Security

License

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Support

data-science-ipython-notebooks has a medium active ecosystem.

It has 25193 star(s) with 7591 fork(s). There are 1632 watchers for this library.

It had no major release in the last 6 months.

There are 16 open issues and 22 have been closed. On average issues are closed in 24 days. There are 17 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of data-science-ipython-notebooks is current.

Quality

data-science-ipython-notebooks has 0 bugs and 0 code smells.

Security

data-science-ipython-notebooks has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

data-science-ipython-notebooks code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

data-science-ipython-notebooks has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

data-science-ipython-notebooks releases are not available. You will need to build from source code and install.

data-science-ipython-notebooks has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

data-science-ipython-notebooks saves you 1710 person hours of effort in developing the same functionality from scratch.

It has 3789 lines of code, 394 functions and 58 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed data-science-ipython-notebooks and discovered the below as its top functions. This is intended to give you an instant insight into data-science-ipython-notebooks implemented functionality, and help decide if they suit your requirements.

Plots a polynomial regression
Fit the model
Called when an event has changed
Calculates the decision surface
Constructor for ResNet50
Constructs the identity block
Convolution block
Contour plot
Overrides options
Plots the separator
Plot a linear regression
Paint a 2d mesh
Plots the k - nearest neighbors of the target
Perform a single step
Calculates the rows from a sequence of ys
VGG19
Prints out the extremes
Make the similarity between two histograms
Logs the probabilities at m
Makes a GPF
VGG16 image
Train a word2vec model
Make the gist
Summarize the evidence
Reads and returns data sets
Parse log line

Get all kandi verified functions for this library.

data-science-ipython-notebooks Key Features

No Key Features are available at this moment for data-science-ipython-notebooks.

data-science-ipython-notebooks Examples and Code Snippets

data-science-ipython-notebooks,license

Jupyter Notebook

Lines of Code : 13

License : Non-SPDX (NOASSERTION)

Copy

Copyright 2015 Donne Martin

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unle

Jupyter Notebook

Lines of Code : 3

License : No License

Copy

Required Reading:

Suggested Reading:

Additional Resources:

running-notebooks

Jupyter Notebook

Lines of Code : 3

License : Non-SPDX (NOASSERTION)

Copy

$ git clone https://github.com/donnemartin/data-science-ipython-notebooks.git
$ cd data-science-ipython-notebooks
$ jupyter notebook

Community Discussions

Trending Discussions on data-science-ipython-notebooks

Convert Firefox bookmarks JSON file to markdown

QUESTION

Convert Firefox bookmarks JSON file to markdown

Asked 2020-Dec-08 at 16:10

Background

I want to show part of my bookmarks on my Hugo website. The bookmarks from Firefox can be saved in JSON format, this is the source. The result should represent the nested structure somehow, in a format of a nested list, treeview or accordion. The source files of contents on the website are written in markdown. I want to generate a markdown file from the JSON input.

As I searched for possible solutions:

treeview or accordion: HTML, CSS and Javascript needed. I could not nest accordions with the tag. Also, seems like overkill at the moment.
unordered list: can be done with bare markdown.

I chose to generate an unordered nested list from JSON. I would like to do this with R.

Input/output

Input sample: https://gist.github.com/hermanp/c01365b8f4931ea7ff9d1aee1cbbc391

Preferred output (indentation with two spaces):

...

ANSWER

Answered 2020-Dec-08 at 16:10

After I watched a few videos on recursion and saw a few code examples, I tried, manually stepped through the code and somehow managed to do it with recursion. This solution is independent on the nestedness of the bookmarks, therefore a generalized solution for everyone.

Note: all the bookmarks were in the Bookmarks Toolbar in Firefox. This is highlighted in the generate_md function. You can tackle with it there. If I improve the answer later, I will make it more general.

Source https://stackoverflow.com/questions/65111588

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install data-science-ipython-notebooks

You can download it from GitHub.
You can use data-science-ipython-notebooks like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.