Link to the paper (https://www.researchgate.net/publication/382264507_A_Survey_of_Machine_Learning_Techniques_for_Artificial_Intelligence)
Machine Learning:
Machine learning allows systems to learn from data and improve their performance over time. Instead of programming a system with strict rules, machine learning algorithms analyze data to discover patterns and relationships.
Use cases:
1- Robotics
2- NLP
3- Finance
Types:
There are types of machine learning.
i)-Supervised learning
In this, the algorithms is trained with labeled data , we get output on the basis of paired input. Common models are SVM and linear regression.
Examples:
Email spam filtering
ii)-Unsupervised learning
In this, the algorithms is trained with unlabeled data , we use it when we unsure of the output. Common models are K-means.
Examples:
Customer segregation
iii)-Reinforcement Learning
In this, the algorithm learns itself from the data and the environment. Common models are PPO and DQN.
Examples:
Robotics
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