Fake news detection using machine learning | Learn with Simple Coding Exercises | kandi tutorial
4AI fake news detector helps detect fake news through binary classification techniques and helps build better experiences by controlling the flow of disinformation. ๐๐ป๐๐๐ฎ๐น๐น ๐๐ตe ๐ญ-๐ฐ๐น๐ถ๐ฐ๐ธ ๐ธ๐ฎ๐ป๐ฑ๐ถ ๐๐ผ๐น๐๐๐ถ๐ผ๐ป ๐ธ๐ถ๐ ๐ผ๐ป ๐๐ฎ๐ธ๐ฒ ๐ก๐ฒ๐๐ ๐๐ฒ๐๐ฒ๐ฐ๐๐ถ๐ผ๐ป ๐ต๐ฒ๐ฟ๐ฒ -https://kandi.openweaver.com/collections/techforgood2022/spotting-fake-news?utm_source=youtube&utm_medium=social&utm_campaign=organic_kandi_ie&utm_content=kandi_ie_kits&utm_term=all_devs
This will install a sandbox Fake News Detection application and all the prerequisites needed for the tutorial. #kandiB4Ucode
The tool works by training a neural network to spot fake articles based on their text content. When you run your own data through the tool, it gives you back a list of articles that it thinks are likely to be fake. You can then train the model further or decide if those results are acceptable or not. In addition to identifying fake news, this model can also be trained to identify real news. This allows you to compare the model's performance across different domains (e.g., politics vs. sports).
We will use fake news detection libraries (having fully modifiable source code) to customize and build a simple classifier that can detect fake news articles. kandi kit provides you with a fully deployable AI Fake News Detector. Source code included so that you can customize it for your requirement.
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#python #machinelearning #fakenewsprediction