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 → j2kao → Fcc_nn_research

j2kao / Fcc_nn_research

Licence: mit
(somewhat) cleaned-up notebooks used in researching public comments for FCC Proceeding 17-108 (Net Neutrality Repeal)

Labels

jupyter-notebooknlp

Projects that are alternatives of or similar to Fcc nn research

Deeplearning tutorials
The deeplearning algorithms implemented by tensorflow
Stars: ✭ 1,580 (+1323.42%)
Mutual labels:  jupyter-notebook
May4 challenge exercises
Original versions of the exercises
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
2048 Api
Educational API for developing ML (imitation learning or reinforcement learning) agents to play game 2048
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
Sphereface
Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17.
Stars: ✭ 1,483 (+1236.04%)
Mutual labels:  jupyter-notebook
Python For Data Analytics
This course will teach you only the relevant topics in Python for starting your career in Data Analytics. There are also a bunch of tips and tricks throughout for resume writing, solving case studies, interviews etc. The idea is to help you land a job in analytics and not just teach you Python.
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
Tutorials2019
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
Py Causal
Stars: ✭ 110 (-0.9%)
Mutual labels:  jupyter-notebook
Deep Learning Language Model
A Code Pattern focusing on how to train a machine learning language model while using Keras and Tensorflow
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
Tsmoothie
A python library for time-series smoothing and outlier detection in a vectorized way.
Stars: ✭ 109 (-1.8%)
Mutual labels:  jupyter-notebook
Vision Ai Developer Kit
Vision AI Developer Kit Preview
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
Algorithms Notebooks
Algorithm's team Jupyter Notebooks
Stars: ✭ 110 (-0.9%)
Mutual labels:  jupyter-notebook
Experiments
Small experiments with attached code
Stars: ✭ 110 (-0.9%)
Mutual labels:  jupyter-notebook
Introduction To Linear Algebra 5th Edition Ee16a
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
Ax
Adaptive Experimentation Platform
Stars: ✭ 1,663 (+1398.2%)
Mutual labels:  jupyter-notebook
Deeplearning.ai Pytorch
PyTorch Implementations of Coursera's Deep Learning(deeplearning.ai) Specialization
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
Natural Language Object Retrieval
Code release for Hu et al. Natural Language Object Retrieval, in CVPR, 2016
Stars: ✭ 110 (-0.9%)
Mutual labels:  jupyter-notebook
Reservoir Engineering
Python worked examples and problems from Reservoir Engineering textbooks (Brian Towler SPE Textbook Vol. 8, etc.)
Stars: ✭ 110 (-0.9%)
Mutual labels:  jupyter-notebook
Elevation
End-to-end guide design for CRISPR/Cas9 with machine learning
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
Firstcoursenetworkscience
Tutorials, datasets, and other material associated with textbook "A First Course in Network Science" by Menczer, Fortunato & Davis
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
K210 tutorial
K210基础入门教程 edit by Kyle阿凯
Stars: ✭ 111 (+0%)
Mutual labels:  jupyter-notebook
View All Similar Projects ➔

fcc_nn_research

(somewhat) cleaned-up versions of notebooks used in researching public comments for FCC Proceeding 17-108 (Net Neutrality Repeal). I am posting the notebook for Exploratory Data Analysis first, and will include others as they are cleaned up.

Where's the data?

See below in the prerequisites section.

Recent Updates (11-27-2017)

4 more notebooks have been uploaded. Run in numerical order to reconstruct the data processing pipeline. Notebook 4 contains the charts. Data for the final couple notebooks is being uploaded and will be linked here tomorrow morning.

Background Information

I did this project as a part of the coursework for Metis and was shocked to see my analysis blow up online. Humbled by the attention but I'm sure experienced data scientists out there could glean even more insights from the work. Please share with the rest of us what else you find in the data! Tweet at me @jeffykao. :-)

Getting Started

This is just a rough sketch of the instructions to the get project up and running on your local machine. Once you get Anaconda installed on your machine, the libraries should be easy to install and the notebooks should be fairly straightforward to run. Instructions to install each library should be easily googlable (sp?).

Prerequisites

Data

First set of data (text and duplicate counts only) posted on kaggle. The README on kaggle will contain links to other versions and subsets of the same dataset.

I'm working hard to get non-text data up as well and will let you know the progress by tweet @jeffykao.

Python/Anaconda version

  • Python 3.6.1 (64-bit)
  • conda 4.3.29

Libraries used

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

  • @drob for putting the blog post on blast and giving me some great advice in the aftermath
  • @leland_mcinnes for authoring HDBSCAN
  • @bekcunning for sending me the link that made me finally write that g***** blog post!
  • @prb_data & Joe Eddy, my instructors at Metis
  • @AndrewDBS who convinced me to get a twitter account
  • My amazing & creative wife/editor who read through & greatly improved my drafts
  • Sweat pants.
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].