 is a model associated with Artificial Intelligence (AI), it helps to perform a task. The tasks are performed by amendment in the system.){kind=link}
Introduction
Machine learning (ML) is a model associated with Artificial Intelligence (AI), it helps to perform a task. The tasks are performed by amendment in the system. The task involves recognition, diagnosis, planning, robot control, prediction, data analysis. Furthermore, it can be said that Machine Learning is a branch of Artificial Intelligence (AI).
Types of ML
There are different types of machine learning:-
Supervised Learning: As the word ‘supervise’ suggests which means to train and analyze. The algorithm is trained and analyzed using label data. After training the model, it begins to make predictions or decisions by giving an input of new data.
Unsupervised Learning: In this type of model, the algorithm learns and makes decisions from the data on its own.
Semi-supervised Learning: As the name suggests, this type of model is a mix of supervised and unsupervised learning. The machine usually learns with a partially labeled dataset. When the input is given new data, it uses its previous learned knowledge to identify it.
Reinforcement Learning: This is the type, the software agents and machines automatically identifies the ideal behavior within a context, to maximize its performance.
Difference Between ML and AI
Machine Learning helps to train the machine without detailed programming whereas AI helps the machine to think and make decisions as human. AI is a subset of ML.
Difference between ML and Deep Learning
Deep Learning uses the multi-layer or neural network to train a machine. It is also considered as a subset of ML
Importance of Machine Learning
1.Machine Learning is required because sometimes there is a need to give output for the specific input to get a desired output.
2. When it comes to data mining, there is a need for specific input and analyze a specific input.
3. The changing machine environment can help to reduce the constant redesign.
4. With this constant modeling, machines will be able to write human knowledge with one explicit code.
Discipline associated with Machine Learning
Machine Learning (ML) can help to analyze the data using statistical models and is used in the neural network. Moreover, Feigenbaum in 1961 used ML for studying the performance of humans in different tasks. Furthermore ,various researchers have developed models for evaluating various AI models. In contrast to this, various evolutionary models for prediction of biology evolution.
Conclusion
ML is a vast field which will help to venture in various fields and help to research the unanswered questions. Although, this is an emerging field with various subset fields as well. There is a long journey to travel and need for skilled employed.
“ML will be light to some unanswered questions.”