Description
Detect fake news with machine learning and feature engineering is a training course on detecting fake news with machine learning and feature engineering, published by Udemy’s online academy. Identifying fake news has become a serious challenge in the age of information overload. Machine learning, along with feature engineering, can be a powerful tool in identifying misleading content. Detecting fake news is an emerging challenge, and using machine learning with thoughtful feature engineering can greatly help in building effective detection models. And learn feature engineering so you can use them to identify fake news.
This training course is a perfect combination of Python and machine learning. In this training course you will learn how to analyze your news and data and then simulate them so that you can determine whether these news are fake or not. This training course is recommended for those who are interested in building fake news detection systems using feature engineering, logistic regression, and machine learning, and those who are interested in detecting emotions and sentiment in fake news using NLP. By completing this training course, you will have a high level of knowledge about machine learning and feature engineering, and you will be able to identify fake news using them.
What you will learn in Detect Fake News with Machine Learning and Feature Engineering:
- How to Build a Fake News Detection Model
- Using feature engineering to predict real or fake news
- Verifying news sources
- Detecting emotions in fake news
- Using Logistic Regression and NLP
- And…
Course Specifications
Publisher: Udemy
coach: Christian Reharj Explained
language English
Level: Introductory to advanced
Number of lessons: 23
Duration: 3 hours 35 minutes
Course Subjects
Detect fake news with machine learning and feature engineering prerequisites
No prior experience in machine learning required
Basic knowledge of Python and Statistics
Pictures
Detect fake news with machine learning and feature engineering intro video
installation Guide
After extract watch it with your favorite player.
Subtitles: none
Quality: 720p
download link
File Password: free download software
size
1.4GB