To begin with, artificial intelligence intelligence is the branch of computer science which study about how to make a computer system automatic. Additionally, like a human brain we make a computer that take a decision by learning from the past experience. Further more, the term intelligence refers that machine makes a decision based on the how they trained. Furthermore, machine learn about the data by different approaches and techniques. This approach commonly divide into two parts supervised and unsupervised. In this article we are more focus on this two algorithms and applications.
Machine Learning Algorithm
As a name suggest using this algorithm machines are trained by using well label training data. For example, if you are training machine for predicting house price you have to pass the price of house at the training phase. On the basis of the supervisor, this algorithm will predict for unseen data. It is one of the most usable algorithm in the field of machine learning. Additionally, there are different type of supervised machine learning algorithm available. But choosing the algorithm is totally depends upon the nature of problem and the data set available. Some popular supervised machine learning algorithms are below.
- Regression: we can use linear regression when there is a relationship between the input and output variable. Mostly, it uses to predict the continuous data such as weather for-casting and stock price predictions. Some regression algorithms are mentioned below.
- Linear Regression
- Non- linear Regression
- Polynomial Regression
- Regression Tree
- Classification: When output variable are in the multiple classes then we used the classification algorithm. For example, when we required a output multiple class such as True or False. Sentiment analysis is one of the most renowned example of the classification algorithm. Some common examples of classification algorithms are.
- Support Vector Machine Learning
- Random Forest
- Naive Bays
- Decision Tree
Instead learning with a help of labeled data unsupervised machine learning algorithm learn without help of teachers. Further, it is totally different than the previous algorithm. We have already supervised algorithm but why we need this, because it helps to find all kind of patterns in out data. It is useful for real time data. The common unsupervised machine learning algorithms are listed below. Finally, clustering is the another name of the unsupervised algorithm.
- K-mean Clustering
- Hierarchal clustering
- K-Nearest Neighbor
Application of Artificial Intelligence
There are tremendous applications of AI some are below.
- Face Mask Detection
- Sentimental Analysis
- Speech Recognization
- Computer Vision
Lastly, this is the end of the article I hope you can get a good lesson from what I deliver in this article. I ask forgiveness for any word and behave which are not to be. Thank you for your kind and attention guys. Stay tuned for the next article. if you are searching for a free python course here is a link. You can run your python code freely in a google Colab here is the link. Last but not list, If you have any questions regarding this article please feel free to comment below.