hougs / Ds For Telco
Licence: apache-2.0
Source material for Data Science for Telecom Tutorial at Strata Singapore 2015
Stars: ✭ 98
Labels
Projects that are alternatives of or similar to Ds For Telco
Talks
Code, slides, and documentation for the talks I have given.
Stars: ✭ 97 (-1.02%)
Mutual labels: jupyter-notebook
Kglab
Graph-Based Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, RDFlib, pySHACL, RAPIDS, NetworkX, iGraph, PyVis, pslpython, pyarrow, etc.
Stars: ✭ 98 (+0%)
Mutual labels: jupyter-notebook
Hmm
An implementation of the Viterbi Algorithm for training Hidden Markov models. This repo accompanies the video found here: https://www.youtube.com/watch?v=kqSzLo9fenk
Stars: ✭ 98 (+0%)
Mutual labels: jupyter-notebook
Lein Jupyter
A Leiningen plugin to integrate clojure with jupyter notebook
Stars: ✭ 97 (-1.02%)
Mutual labels: jupyter-notebook
Estimation Of Remaining Useful Life Using Cnn
Convolutional Neural Network based regression approach for estimating machinery's remaining useful life
Stars: ✭ 98 (+0%)
Mutual labels: jupyter-notebook
Bigdata
NJU Master Course **Big Data Mining and Analysis**
Stars: ✭ 98 (+0%)
Mutual labels: jupyter-notebook
Graph2nn
code for paper "Graph Structure of Neural Networks"
Stars: ✭ 98 (+0%)
Mutual labels: jupyter-notebook
Food 101 Mobile
Deep Learning Food Classifier for iOS using Keras and Tensorflow
Stars: ✭ 97 (-1.02%)
Mutual labels: jupyter-notebook
Interaction network pytorch
Pytorch Implementation of Interaction Networks for Learning about Objects, Relations and Physics
Stars: ✭ 98 (+0%)
Mutual labels: jupyter-notebook
Keras Tutorial
Tutorial teaching the basics of Keras and some deep learning concepts
Stars: ✭ 98 (+0%)
Mutual labels: jupyter-notebook
Droneblocks Tello Python
A DroneBlocks course on drone programming with Tello using Python scripts
Stars: ✭ 98 (+0%)
Mutual labels: jupyter-notebook
ds-for-telco
Source material for Data Science for Telecom Tutorial at Strata Singapore 2015
The source notebook demonstrates building a churn prediction model using Spark and Spark MlLib's pipeline API for cross validation and model tuning. The Pipeline API is available in PySpark in version 1.6 or higher.
The source ipython notebook can be displayed as slides. If you have ipython installed you can serve the slides locally with:
ipython nbconvert ds-for-telco.ipynb --to slides --post serve
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].