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What is Fake News?
Fake news is the deliberate presentation of (typically) false or misleading claims as news, where the claims are misleading by design.
How News and digital media evolved?
The news media evolved from newspapers, tabloids, and magazines to a digital form such as online news platforms, blogs, social media feeds, and many news mobile apps. News outlets benefitted from the widespread use of social media/mobile platforms by providing updated news in near real time to its subscribers.
It became easier for consumers to acquire the latest news at their fingertips. So, These digital media platforms become very powerful due to their easy accessibility to the world and ability to allow users to discuss and share ideas and debate over issues such as democracy, education, health, research and history.
However, apart from advantage, false/fake news articles on digital platforms are getting very common and mainly used with a negative intent for their own benefit such as political and financial benefit, creating biased opinions, manipulating mindsets, and spreading absurdity.
How big is this Problem ?
With the rapid adoption of Internet, social media and digital platforms (such as Facebook, Twitter, news portals or any social media), anybody can spread untrue and biased information. It is virtually impossible to prevent Fake News from being created. There has been a rapid increase in the spread of fake news in the last decade, it's not limited to any one domain like politics but covering various other domains such as sports, health, history, entertainment and also science and research. If we take the 2016 US presidential election, there were lots biased and fake news published to influence. Another example could be of COVID-19, we generally come across many misleading/fake news everyday which can have serious consequences and may lead to create panic among people and spread pandemic more rapidly.
What is Solution?
Therefore, It is important and absolutely necessary to identify and differentiate Fake News from real news. One of the ways is to determine by expert and fact check of every news, but this is time consuming and requires skills which can not be shared. Second, we can automate the detection of Fake News by using the techniques of Machine learning and Artificial Intelligence. The Online news content has diverse unstructured format data(such as documents, videos, and audios), here we will concentrate on text format news. With the advancement of and Natural language processing It is possible now that we can identify the deceptive and fake nature of articles or sentences.
There is widespread study and experimentation happening in this area to identify the Fake news for all medium(Video, audio and Text) news.
In our study we used the Fake news dataset from Kaggle to classify unreliable news articles as Fake news using Deep learning Technique Sequence to Sequence programming.
A full training dataset with the following attributes
In this deep learning project, you will learn how to build your custom OCR (optical character recognition) from scratch by using Google Tesseract and YOLO to read the text from any images.
The goal of this apache kafka project is to process log entries from applications in real-time using Kafka for the streaming architecture in a microservice sense.
In this Databricks Azure tutorial project, you will use Spark Sql to analyse the movielens dataset to provide movie recommendations. As part of this you will deploy Azure data factory, data pipelines and visualise the analysis.
In this PySpark project, you will simulate a complex real-world data pipeline based on messaging. This project is deployed using the following tech stack - NiFi, PySpark, Hive, HDFS, Kafka, Airflow, Tableau and AWS QuickSight.
In this spark project, you will use the real-world production logs from NASA Kennedy Space Center WWW server in Florida to perform scalable log analytics with Apache Spark, Python, and Kafka.
In this deep learning project, you will find similar images (lookalikes) using deep learning and locality sensitive hashing to find customers who are most likely to click on an ad.
Learn to design Hadoop Architecture and understand how to store data using data acquisition tools in Hadoop.
Hive Project -Learn to write a Hive program to find the first unique URL, given 'n' number of URL's.
In this Deep Learning Project on Image Segmentation Python, you will learn how to implement the Mask R-CNN model for early fire detection.
In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.