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In the world, there are many rare and incurable diseases that need to be detected. The manual detection of those diseases requires more cost and time. Autism is one of the main diseases that are increasing at a higher rate and its detection techniques are very challenging. But the early detection of autism can save a patient or increase their lifetime. So this work concentrates on developing machine learning algorithms to detect autism. Our project's main aim is to detect whether the patient is having autism or not. The appropriate dataset is used with eight machine learning algorithm and their performance are evaluated to find the best algorithm for autism detection.