• Priyanka Jadhav
• Amruta Ladgaonkar
• Kaivalya Patil
• Shivani Dive
• Prof. Nakul Sharma

Criminal activities are present in every region of the world affecting the quality of life along with the social and economic development of the country. Thus, there is an urgent need for security representatives and agencies to fight and reduce crime. Many governments are trying to use advanced techniques to tackle such issues. Crime prediction practices historical data and after examining data, predicts the upcoming crime concerning location, time, day, season and year. The main aim of this paper is to describe a summary of the computational techniques that has been implemented toward crime data analysis and prediction. The survey of different techniques is performed besides with an abstract view of the proposed system that we are going to implement. The proposed system helps to predict and solve crimes at a much faster rate using machine learning techniques to reduce the crime rate. The system helps to prevent crimes or to improve the investigation efforts.

Crime Rate Analytics, Machine eLearning Approach, Crime Prevention, crime types, prediction model, Data Collection, Dependent Variable Analysis, Word2Vector Formation, and Algorithm Analysis.

"A Machine learning Approach for Crime Rate Analytics: Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 2, page no.376-381, February-2021, Available :http://www.jetir.org/papers/JETIR2102041.pdf

"A Machine learning Approach for Crime Rate Analytics: Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 2, page no. pp376-381, February-2021, Available at : http://www.jetir.org/papers/JETIR2102041.pdf