Often we get confused between different types of Supervised learning models available. This is majorly due to lack of understanding of the goal and applicability of each kind of model. In this blogpost, I will try to clarify the difference and purpose of each kind of Supervised learning model using a common example across all these models. Apart from defining each model type, I will also mention if any models could be used interchangeably for certain scenarios. Types of Supervised Learning Models Understanding Models using an Example Let’s use the example of predicting whether a person has diabetes based on […]
Comparative Assessment of Critical AI Models
This blog post is a one stop platform for summary of different AI models that are in predominant use. The comparative assessment of these models is based on various parameters such as – Definition, Process, Main Learning Approach, Pros, Cons, and Applications. The idea is to summarize these models and make it available for a quick view. Note that the information about the model’s is not limited to the contents in this post. Readers are highly encouraged to refer valid sources for additional and detailed information. ModelDefinitionProcess Main Learning ApproachProsConsApplicationsLinear RegressionA model that predicts a continuous output by finding the […]
ChatGPT: Assignment companion
With all the hype going on lately about ChatGPT, it has become the talk of every household. While a certain clan is reaping its benefits, there are some who are either exploring its breaking point or misusing it incessantly at various degrees. Starting from misusing it for assignments to generating malwares, ChatGPT seems to have become the Messiah lately and is here to stay. You might think this blog is written using ChatGPT as well. While it could have been possible, but that would not have involved the sentience of a human which even ChatGPT acknowledges of in its various […]
Machine “Un”learning
With increasing concern for data privacy, there have been several measures taken up to make AI applications privacy friendly. Of many such measures, the most commonly found and practiced method is Federated Learning. While an entire blog post will be dedicated to know how it works and its current application, this post is about yet another least discussed and probably a more theoretical approach as of now, and that is Machine Unlearning. There have been limited yet substantial research work done in this domain with diverse approaches used by the researchers to attain the objective. As the name suggests, an […]
Artificial Intelligence and Cryptography: An Intersection
There has been this common belief among a large sector of academicians and researchers about Artificial Intelligence (AI) and Cryptography – “They are not relatable” or “There is nothing about Cryptography that AI can do.” Up until times when AI was still quite invisible, one might have continued believing the domains to be mutually exclusive. But is this belief still intact? Let’s find out. Ronald L. Rivest in year 1991 published his work Cryptography and Machine Learning where he brings out not only the relationship between both domains but also how each one influences another. Furthermore he also mentions how […]