There is water waste associated with the typical irrigation method since it uses a significant amount of liquid. A clever watering setup is desperately needed to minimize the amount of liquid waste on this tedious task. In the era of machine learning (ML) and the Internet of Things (IoT), it is great to have an intelligent system that can perform this task autonomously with minimal help from people. With the modest assistance of farmers, an enabled Internet of Things machine learning recommendation system is suggested in this work for effective water use. The exact collection of ground and environmental data in crop fields is achieved by the deployment of IoT sensors. The collected data are sent to and saved on a server in the cloud, which employs machine learning techniques to assess the information and recommend irrigation to the farmer. This recommendation system has an integrated feedback mechanism added to it to make it robust and flexible. Tests demonstrate the effectiveness of the proposed system rather well on the agricultural dataset as well as our dataset.