Agriculture is the backbone of the economy. It provides for more than just the necessities of life for people; in underdeveloped nations, it also provides work. There is a reduction in the crop yield and quality. This leads to scarcity of food. The improved technologies like Machine Learning (ML), and the Internet of Things (IOT) are applied in agriculture to overcome the challenges in agriculture. IOT devices like sensors are used in the field to collect soil parameters. Based on sensor-collected data, the ML model recommends the suitable crop for cultivation, which gives good yield and profit to the farmers. Hybrid algorithms are used to perform analysis over the dataset and provide results. In this survey, we examine the previous research work various authors have carried out on implementing IOT and ML in several agricultural principles. Keywords— Internet of Things (IoT), Machine Learning (ML)