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 → llSourcell → Logistic_regression

llSourcell / Logistic_regression

This is the code for "Logistic Regression" By Siraj Raval on Youtube

Labels

jupyter-notebook

Projects that are alternatives of or similar to Logistic regression

Leveling Up Jupyter
Leveling up your Jupyter notebook skills
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Reverse Engineering Neural Networks
A collection of tools for reverse engineering neural networks.
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Ai Pizza
Stars: ✭ 79 (+0%)
Mutual labels:  jupyter-notebook
Noaa Ghcn Weather Data
Fetching and processing NOAA Global Historical Climatology Network Weather Data
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Cubehelix
A full implementation of Dave Green's "cubehelix" colormap for Python
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
1806
18.06 course at MIT
Stars: ✭ 1,219 (+1443.04%)
Mutual labels:  jupyter-notebook
Learning python
Source material for Python Like You Mean it
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Chi course 2019
ACM SIGCHI 2019 Course on Bayesian Methods for Interaction
Stars: ✭ 79 (+0%)
Mutual labels:  jupyter-notebook
Skogestad Python
Python code for "Multivariable Feedback Control"
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Covid 19 jhu data web scrap and cleaning
This repository contains data and code used to get and clean data from https://github.com/CSSEGISandData/COVID-19 and https://www.worldometers.info/coronavirus/
Stars: ✭ 80 (+1.27%)
Mutual labels:  jupyter-notebook
Dm Competition Getting Started
数据挖掘竞赛(Kaggle,Data Castle,Analytics Vidhya,DrivenData)入门实践
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Notebooks
A collection of Jupyter/IPython notebooks
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Ctpn
Detecting Text in Natural Image with Connectionist Text Proposal Network (ECCV'16)
Stars: ✭ 1,220 (+1444.3%)
Mutual labels:  jupyter-notebook
Machine Learning
My Attempt(s) In The World Of ML/DL....
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Time Series Prediction Lstm Pytorch
Time Series Prediction with LSTM Using PyTorch
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Tutorials 2018
Geophysical Tutorials column for 2018
Stars: ✭ 78 (-1.27%)
Mutual labels:  jupyter-notebook
Sms Tools
Sound analysis/synthesis tools for music applications
Stars: ✭ 1,215 (+1437.97%)
Mutual labels:  jupyter-notebook
Pose Estimation tutorials
Tools and tutorials of pose estimation and deep learning
Stars: ✭ 79 (+0%)
Mutual labels:  jupyter-notebook
Microsoft Ai Curriculum
Microsoft AI Curriculum Hungary
Stars: ✭ 79 (+0%)
Mutual labels:  jupyter-notebook
Adventures In Tensorflow Lite
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
Stars: ✭ 79 (+0%)
Mutual labels:  jupyter-notebook
View All Similar Projects ➔

Sentiment Analysis with Logistic Regression

Overview

This is the code for this video on Youtube by Siraj Raval.

This repository contains a jupyter notebook and the necessary data to implement sentiment analysis of tweets using Logistic Regression. Please open the notebook for more information.

The dataset

The dataset was obtained from a Kaggle competition. The dataset is divided into a train and a test dataset. Each record contains the following fields:

Field name Meaning
ItemID id of twit
Sentiment sentiment (1-positive, 0-negative)
SentimentText text of the twit

Web app

You can go straight ahead and try out the algorithm with a small web app I have included in this repository, just run:

cd site
python app.py

Then open a browser in the default address (http://127.0.0.1:5000/) and play around:

web

Requirements

This notebook will run in Python >= 3.5. The following packages are required:

  • bokeh
  • flask
  • nltk
  • numpy
  • pandas
  • scikit-learn

Limitations

Because the training set contains only English twits, this classifier will only work with English twits.

Credits

Credits for this code go to guillermo-carrasco

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].