From 8fa0d4cc58b844d84f7b1bf6f269162b645a2f0d Mon Sep 17 00:00:00 2001 From: Navan Chauhan Date: Mon, 23 Nov 2020 19:39:48 +0530 Subject: Publish deploy 2020-11-23 19:39 --- posts/2019-12-22-Fake-News-Detector/index.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'posts/2019-12-22-Fake-News-Detector') diff --git a/posts/2019-12-22-Fake-News-Detector/index.html b/posts/2019-12-22-Fake-News-Detector/index.html index 14c4770..f6dbc67 100644 --- a/posts/2019-12-22-Fake-News-Detector/index.html +++ b/posts/2019-12-22-Fake-News-Detector/index.html @@ -1,4 +1,4 @@ -Building a Fake News Detector with Turicreate | Navan Chauhan
Navan Chauhan
7 minute readCreated on December 22, 2019Last modified on September 15, 2020

Building a Fake News Detector with Turicreate

In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app

Note: These commands are written as if you are running a jupyter notebook.

Building the Machine Learning Model

Data Gathering

To build a classifier, you need a lot of data. George McIntire (GH: @joolsa) has created a wonderful dataset containing the headline, body and whether it is fake or real. Whenever you are looking for a dataset, always try searching on Kaggle and GitHub before you start building your own

Dependencies

I used a Google Colab instance for training my model. If you also plan on using Google Colab then I recommend choosing a GPU Instance (It is Free) This allows you to train the model on the GPU. Turicreate is built on top of Apache's MXNet Framework, for us to use GPU we need to install a CUDA compatible MXNet package.

!pip install turicreate
+Building a Fake News Detector with Turicreate | Navan Chauhan
Navan Chauhan
7 minute readCreated on December 22, 2019Last modified on September 15, 2020
Building a Fake News Detector with Turicreate
In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app
Note: These commands are written as if you are running a jupyter notebook.
Building the Machine Learning Model
Data Gathering
To build a classifier, you need a lot of data. George McIntire (GH: @joolsa) has created a wonderful dataset containing the headline, body and whether it is fake or real. Whenever you are looking for a dataset, always try searching on Kaggle and GitHub before you start building your own
Dependencies
I used a Google Colab instance for training my model. If you also plan on using Google Colab then I recommend choosing a GPU Instance (It is Free) This allows you to train the model on the GPU. Turicreate is built on top of Apache's MXNet Framework, for us to use GPU we need to install a CUDA compatible MXNet package.
!pip install turicreate
 !pip uninstall -y mxnet
 !pip install mxnet-cu100==1.4.0.post0
 
If you do not wish to train on GPU or are running it on your computer, you can ignore the last two lines
Downloading the Dataset
!wget -q "https://github.com/joolsa/fake_real_news_dataset/raw/master/fake_or_real_news.csv.zip"
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