Architecture of Data Recognition System Using Machine Learning and TensorFlow

This research study analyzed how the structure of software architecture is applied in image recognition process in the field of data science and mainly focus on the concept of image recognition is, the types of data required and the scope of the volume of data needed for the undertaking. In general concepts behind data science will be explained, such as how the data is processed into a usable format, and the strategies used to categorize and sort the data. Architecture of tools used analyze the image recognition, their functionalities and why python is commonly used for processing large amounts of data like TensorFlow and Keras. This study analyses both the functional and non-functional requirements that image recognition require of thes e tools and how they are achieved