MACHINE LEARNING-Machine Learning is a field of Artifical Intelligence
Machine Learning is a field of Artifical Intelligence that focuses on enabling computers to learn from data without being explicitly programmed. It involves creating algorithms that can analyze patterns in data and take predictions or decisions with minimal human intervention.
Types of Machine Learning
1. Supervised learning:
Algorithms learn from labeled data, where the desired output is known, and predict outputs for new inputs.
2. Unsupervised learning:
Algorithms learn from unlabeled data, where the desired output is not known, and discover patterns or structure in the data.
3. Reinforcement learning:
Algorithms learn by interacting with an environment and receiving rewards or penalties for their actions.
Applications of Machine Learning
· Image and speech recognition :
Recognizing images and speech, as seen in applications like self-driving cars and voice assistants.
· Fraud detection:
Identifying fraudulent transactions or activity.
· Personalized recommendations:
Suggesting products, movies, or other content based on user preferences.
· Medical diagnosis:
Assisting in the diagnosis of diseases.
· Natural language processing:
Understanding and generating human language.
Advantages of Machine Learning
- · Automation of Repetitive Tasks
- · Improved Accuracy and Efficiency
- · Data-Driven Decision-Making
- · Pattern Recognition and Trend Identification
- · Continuous Improvement
- · Cost Efficiency
- · Innovation Enablement
- · Scalability
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