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This research proposes early prediction of stroke disease using different machine learning approaches such as Logistic Regression Classifier, Decision Tree Classifier, Support Vector Machine and Random Forest Classifier. In this paper we have used different Machine Learning algorithm and by calculating their accuracy we are proposing fair comparisons of different Stoke prediction algorithms by using same dataset with same no of features. The researcher will help to predict the Stroke using best Machine Learning algorithm.

Inability to talk is taken into account to be true incapacity. folks with this incapacity use totally different modes to speak with others, there are variety of strategies accessible for his or her communication one such common methodology of communication is language. Developing language application for speech impaired folks is vital, as they’ll be ready to communicate simply with even people who don’t perceive language. Our project aims at taking the fundamental step in bridging the communication gap between traditional folks, deaf and dumb folk’s victimization language. the most focus of this work is to form a vision-based system to spot language gestures in real-time. Not solely that, however our project conjointly aims to focus on the audience or the users with very little or no data regarding any language. The project can aim to be helpful for each the traditional yet because the person with speaking or hearing incapacity. Although, the scope of the project shall be on the far side the compatibility, still it's herewith tried to usher in the module or a locality of the appliance for the speech impaired person. Future scope of the project aims to develop the appliance to assist person with all ability. Keywords: Hand Sign Recognition, American-Sign-Language, Yolo, Object Detection, Gesture to Speech, CNN, Machine Learning.

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