The below is an excerpt of a longer article. Feel free to check out the full article at AtoZ Markets.

Alan Turing, in 1947 said that “what we want is a machine that can learn from experience.” His words can be marked true today as we have Deep Learning. It is a new machine learning technique that imitates the way we human beings gain knowledge and learn through examples.

What is Deep Learning?

Deep learning is one of the branches of machine learning in the field of Artificial Intelligence, commonly known as AI. Deep learning includes statistics and predictive modeling, and hence it is an essential element of data science.

Deep learning makes the process faster and easier, especially when it comes to tasks related to data science like collect, analyzing, interpreting, and everything that deals with working on a large amount of data. Let us discuss a few of the topmost and widespread applications of Deep Learning.

Fraud News Detection and News Aggregation

Every day, The internet is becoming the primary source of all genuine and fake information. Fraud news detection has become an essential asset in today’s world. It has become challenging to distinguish between the false and the real news as bots replicate it across channels automatically. Cambridge Analytica is one of the best examples of how personal information, fake news, and statistics can influence reader perception.

Deep learning helps develop filters or classifiers that can detect fake news and remove it from the feed. It can also warn you of possible privacy breaches. It is challenging and complicated to train and validate a deep learning neural network for news detection since the data is cursed with opinions. The news is neutral or not and is not decided by one party.

Earlier, we never had an option to filter out the ugly and bad news from the news feed. Extensive use of deep learning in the aggregation of news is strengthening efforts to customize reports as per readers’ choice. It might not sound like something new, but if we need to define the reader persona, further sophistication levels are being met to filter out news as per geographic, economic, social parameters, and the personal preference of the reader.

For those looking for further insight, check out the full article on What Are Some Deep Learning Applications in 2021?