Use cases of Neural Networks

A neural network is a series of algorithms that is designed to find the hidden features from a set of data nearly like the way the human brain operates. Neural network are called after the organic neurons as the structure of the neural networks represents the neurons. These neural networks can change the prediction when the input is passed on to training to develop a model to improve the prediction with less errors.

Neural networks are used for modern data which are big in size and are called the Big Data. When we work with traditional machine learning model, it works better will smaller records of data. But as we go on increasing the data the model will be overfitted and leads to wrong answers

• As we can see from the above graph, the performance for the smaller data sets, Older model is slightly better than the new deep learning models but as the data increases, the performance doesn’t change anymore leading to more wrong prediction and errors sometimes.
• Neural networks works good with the image processing and object detection because the images come into larger data will thousands of fields and millions of records of data which older models cannot handle.
  These neural networks can be used in object detection from the images or videos and also can be used for time series data which is also sometimes big data to process.
• Neural networks are broadly used, with applications for financial operations, enterprise planning, trading, business analytics and product maintenance
• Voice assistants or chatbots also need neural networks because of the complexity of the data and needs a high amount of computing which is not efficient with old ML algorithms.
• ANNs are widely used for medical applications in various disciplines of medicine especially in cardiology. ANNs have been extensively applied in diagnosis, electronic signal analysis, medical image analysis and radiology.
• Neural networks can also be used in creating simulations and modelling which can accelerate the speed of testing of products with lower costs compared to physical testing which may take a lot of resources.
• Neural network can also be used in security by checking all the logs of the servers which are very large datasets to check for dummy requests and block those users who are trying to make multiple requests to do a DoS attack or to send malware to the servers.

I hope you found this article useful and enjoyed it 😄