Livewire-Coimbatore Ram nagar

  Machine learning Life cycle Machine learning has given the computer systems the abilities to automatically learn without being explicitly programmed. But how does a machine learning system work? So, it can be described using the life cycle of machine learning. Machine learning life cycle is a cyclic process to build an efficient machine learning project. The main purpose of the life cycle is to find a solution to the problem or project. Machine learning life cycle involves seven major steps, which are given below: Gathering Data Data preparation Data Wrangling Analyze  Data Train the model Test the model Deployment 1. Gathering Data: Data Gathering is the first step of the machine learning life cycle. The goal of this step is to identify and obtain all data-related problems. In this step, we need to identify the different data sources, as data can be collected from various sources such as  files ,  database ,  internet , or  mobile devices . It is one of ...

  Applications of Machine learning 1. Image Recognition: Image recognition is one of the most common applications of machine learning. It is used to identify objects, persons, places, digital images, etc. The popular use case of image recognition and face detection is,  Automatic friend tagging suggestion : Facebook provides us a feature of auto friend tagging suggestion. Whenever we upload a photo with our Facebook friends, then we automatically get a tagging suggestion with name, and the technology behind this is machine learning's  face detection  and  recognition algorithm . It is based on the Facebook project named " Deep Face ," which is responsible for face recognition and person identification in the picture. 2. Speech Recognition While using Google, we get an option of " Search by voice ," it comes under speech recognition, and it's a popular application of machine learning. Speech recognition is a process of converting voice instructions into text,...