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Chatbots are being used in a wide variety of industries, ranging from industry to education. It is not as effective when using traditional ways of developing a chatbot system as it is when using machine learning (ML). Historically, they were created using finite-state machines, rule-based systems, and knowledge bases. Although these technologies had shortcomings, they were nonetheless employed to create chatbots. This is because natural language processing and neural network technology have simplified the task of conversational AI systems categorizing intentions and locating persons and places. Many people have asked us how we created an Arabic chatbot that understands real language, and we'd like to demonstrate how we achieved it. It is capable of responding, acting on behalf of the user, and retaining the context of a communication between two persons. We employed models such as FastText and BERT, which may be used in multiple languages concurrently. Additionally, we employed two pipeline components that we created specifically for this project. [ABSTRACT FROM AUTHOR]

When the flow of blood in any section of the brain is interrupted, a brain stroke happens. If blood flow is stopped prolonged period of time,the brain is depleted of blood and oxygen, brain cells can perish, which impairs the functions controlled by that area of the brain. Estimating the likelihood of an illness or diagnosis, assessing the prediction or result of diseases, and supporting physicians in prescribing therapy for diseases are just a few of the numerous prediction methods that have been extensively used when making clinical decisions. However, due to their inability to simulate the difficulty of feature representation in the healthcare issue domains, standard predictive models or techniques are still insufficient for capturing the underlying knowledge. The classifier from Adaboost was used on a dataset a cardiac condition in this study to report predictive analytical techniques for stroke illnesses. Atrial fibrillation signs and symptoms in people with heart disease are a significant risk element for stroke, and they share the same factors to anticipate stroke. The results of this study is more precise than existing medical grading procedures for alerting cardiac patients who are at risk for stroke. [ABSTRACT FROM AUTHOR]

Online transactions and shopping make the life of urban cities more comfortable. But this system is not full proof there are various flaws due to which hacker can steal all the hard-earned money is very less amount of time. The need for earlier detection of online frauds is increasing day by day. Online fraud refers to frauds when product bought online is of cheap quality or the money from one account is robbed. In this paper, we are going to discuss various types of online-based frauds and their detection using machine learning. Accuracy is also an important factor while discussing online frauds in this paper we are also going to discuss various methods used to calculate the accuracy. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is a term used to describe a group of neurodevelopmental abnormalities. Differences in communication and social interaction are characteristics of these disorders. People with ASD may have limited and repetitive hobbies or behavioural patterns.ASD affects people of all races & ethnicities, cultures, and socioeconomic backgrounds. Early infancy is when ASD symptoms typically appear, usually between the ages of 12 and 24 months. Symptoms, on the other hand, could appear at any time. A severe delay in linguistic or social development could be one of the first indicators. Autism involves symptoms relating to physical movements and behaviours and speech and social difficulties. It's unclear why autism occurs. It might be caused by issues in the regions of your brain that interpret sensory information and process language. It may happen to persons of any race, nationality, or social status. The proposed study is reviewed to identify the autistic disorder and detect this ASD problem using machine learning, as well as to conclude the behavioral features of human nature during ASD. [ABSTRACT FROM AUTHOR]