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

 by   donnemartin Python Version: Current License: Non-SPDX

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

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.

            kandi-support 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.

            kandi-Quality Quality

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

            kandi-Security 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.

            kandi-License 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.

            kandi-Reuse 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

            Jupyter Notebookdot img1Lines of Code : 13dot img1License : Non-SPDX (NOASSERTION)
            copy iconCopy
            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
            <a rel="nofollow"></a>,<a rel="nofollow"></a>
            Jupyter Notebookdot img2Lines of Code : 3dot img2no licencesLicense : No License
            copy iconCopy
            Required Reading:
            Suggested Reading:
            Additional Resources:
            Jupyter Notebookdot img3Lines of Code : 3dot img3License : Non-SPDX (NOASSERTION)
            copy iconCopy
            $ git clone
            $ cd data-science-ipython-notebooks
            $ jupyter notebook

            Community Discussions

            Trending Discussions on data-science-ipython-notebooks


            Convert Firefox bookmarks JSON file to markdown
            Asked 2020-Dec-08 at 16:10

            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 sample:

            Preferred output (indentation with two spaces):



            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.


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


            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.


            Contributions are welcome! For bug reports or requests please submit an issue.
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