Measuring and monitoring Blood Pressure for cardiovascular patients is critical and essential too. A variation in heart rate is very important for a patient’s physiological condition analysis. But using cuff every time for measuring Blood Pressure, passing electrical signal to monitor Heart rate may irritate the patient. This idea provides cuff less measurement of Blood Pressure and Heart rate measurement using Photoplethysmography only. Arterial Blood Pressure and Photoplethysmogram along with Electrocardiogram is the most popular methods of measuring Cardio Vascular Status these days. Mostly both ABP and PPG together perform operations like monitoring Blood pressure with high efficiency and ECG for Heart rate. Measuring Heart rate from ECG and Blood Pressure from ABP may cause discomfort to the subject. So, we implement only PPG based system to monitor Both Blood Pressure and Heart rate. Now a days, Internet of Things, Cloud, Artificial Intelligence, and Machine Learning are taking their place everywhere to reduce the man power and ease the computations in automating this world. We detect the PPG signal and transfer the data to cloud in order to apply the Machine Learning algorithm to measure the Blood pressure and Heart rate. This paper gives about the various Machine learning ideas of measuring Blood Pressure along with Heart rate. We used Support Vector Regression, Random Forest, Decision Tree, Adaboost and Adaboost hyper tuning algorithms of machine learning for prediction of Blood Pressure and resulted with high accuracy in Decision Tree and Adaboost algorithms among all the five algorithms tried.