Study includes information about the recommendation system using Machine Leaning. The Recommendation system could recommend the whole thing from songs, movies, jokes, restaurants with rankings. That may collect the relevant data from the web. And give a relevant outcome to the user. The author using a Collaborative Filtering technique is a basic path of any recommendation System. But only Collaborative Filtering cannot give sufficient result about scalability and accuracy and also provide a computation of sample value of the evaluation prediction and measures for evaluating the algorithm. The major consciousness of this paper, the author provides the methodology of Data Pre-processing, Singular Value Decomposition (SVD), Content-based Collaborative filtering algorithm based on the recommendation system. The similarity is determined using for a Collaborative Filtering (CF) set of rules based totally on person similarity, behaviour and personalized movie recommendation system. And this consists of an analysis of the outcomes and conclusions based totally at the simulations executed on the computer to assess how the algorithms work

Data Preprocessing, Singular Value Decomposition(SVD), Content based Collaborative Filtering Algorithm

in big data”,9th International Conference on, Intelligent Systems and Control (ISCO), Sept 2015, pp 1-7.
[2] Swati Mittal Singal, Tejal, Bhawna Juneja “AdaBoosting for Case-Based Recommendation System” ,IEEE 2016.
[3] Sonali R. Gandhi, Prof. Jaydeep Gheewala “A Survey on Recommendation System with Collaborative Filtering using Big Data” ,ICIMIA ICIMIA 2017 International Conference Innovative Mechanism IndustryApplications.
[4] Sasmita Panigrahi, Rakesh Ku. Lenka, Ananya Stitipragyan, “A Hybrid Distributed Collaborative Filtering Recommender Engine Using Apache Spark”, Procedia Computer Science, 2016
[5] Karan Patel, Yash Sakaria and Chetashri Bhadane, “Real Time Data processing Framework”, International Journal of Data Mining and Knowledge Management Process (IJDKP) Vol.5, No.5, September 2015.
[6] Michael Stonebraker, Uur etintemel, Stan Zdonik, “The 8 Requirements of Real-Time Stream Processing”, IEEE 2017.
[7] Ms. Nishigandha Karbhari, Prof. Asmita Deshmukh ,Prof. Asmita Deshmukh “Recommendation System using Content Filtering” ,International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS-2017) .
[8] Ibrahim Hussein Mwinyi, Husnu S. Narman, Kuo-Chi Fang, and Wook-Sung Yoo “Predictive Self-Learning Content Recommendation System for Multimedia Contents”, WTS 2018 1570426345.
[9] Gopi Krishna Durbhaka, Barani Selvaraj “Predictive Maintenance for Wind Turbine Diagnostics using Vibration Signal Analysis based on Collaborative Recommendation”, Approach 2016 Intl. Conference on Advances in Computing, Communications and Informatics (ICACCI), Sept. 21-24, 2016, Jaipur, India.
[10] De˘ger Ayata, Yusuf Yaslan and Mustafa E.Kamasak “Emotion Based the Music Recommendation System Using Wearable Physiological Sensors” ,IEEE 2018.
[11] Ruchika1, Ajay Vikram Singh2, Mayank Sharma3. “Building an Effective Recommender System Using Machine Learning Based Framework”,@IEEE 2018.
[12] Wisuwat Sunhem Kitsuchart Pasupa “An Approach to Face Shape Classification for Hairstyle Recommendation”, 8th International Conference on Advanced Computational Intelligence Chiang Mai, Thailand; February 14- 16, 2016
[13] Fabiano A. Dorc¸a1, Vitor C. Carvalho1, Miller M. Mendes1, Rafael D. Ara´ujo1, Hiran N. Ferreira2, Renan G. Catellan1 “An Approach for Automatic and Dynamic Analysis of Learning Objects Repositories Through Ontologies and Data Mining Techniques for Supporting Personalized Recommendation of Content in Adaptive and Intelligent Educational Systems”, 2017 IEEE 17th International Conference on Advanced Learning Technologies
[14] Anurag Gulati Anish Batra Rohit Khurana Dr. MM Tripathi “Cognitive Learning Recommendation System in Indian Context” ,978-1- 5386-1922-3/17/$31.00 © 2017 IEEE
[15] Joseph Coelho, Paromita Nitu, and Praveen Madiraju “A Personalized Travel RecommendationSystem Using social Media Analysis” ,2018 IEEE International Congress on Big Data
[16] Sasmita Panigrahi, Rakesh Ku. Lenka, Ananya Stitipragyan, “A Hybrid Distributed Collaborative Filtering Recommender Engine Using Apache Spark”, Procedia Computer Science, 2016, pp 10001006.
[17] Lipi Shah, Hetal Gaudani and Prem Balani, “A Survey on Recommendation System”, International Journal of Computer Applications(IJCA),March 2016, pp. 43-49.
[18] A. D. a. V. S. N. Karbhari, “Recommender System in Machine Learning” , ICEMTE, vol. 5, no. 3, pp. 62-65, 2017. International.
[19] Ahmed, Muyeed, et al. “TV Series Recommendation Using Fuzzy Inference System, K-Means Clustering and Adaptive Neuro Fuzzy Inference System” ,2017, pp. 1512–1519.
[20] Robert J. Durkin, AakashVerma. “Experiential Learning in Engineering Technology”, A Case Study on Problem Solving in Project-Based Learning at the Undergraduate Level", Journal of Engineering Technology, 2016.