This blog brief's about Machine Learning and its types.
Machine Learning is part of artificial intelligence that successfully automates the process of developing analytical models and enables machines to adapt to different settings.
Applications:
- Diagnosis of Diseases
- Vision(identifies what object it is, when object is given)
- Financial Forecasting
- Identifying price Sensitivity
- Fraud Detection
→ Those are some applications of Machine Learning.
→ There are 4 types of Machine Learning(ML)
- Supervised Learning
- Unsupervised Learning
- Semi-Supervised Learning
- Reinforcement Learning
1.Supervised Learning:
→ Supervised Learning is used for Labeled data.(Have 100% knowledge on data)
→ Supervised Learning is of 6 types
- Regression
- Classification
- Naive Bayesian Model
- Random Forest Model
- Neural Networks
- Support Vector Machine
2.Unsupervised Learning:
→ Unsupervised Learning is used for Non-Labeled data.(Have 0% knowledge on data)
→ Unsupervised Learning is of 2 types
- Clustering
- Association
→ Clustering:
- K-means Algorithm
- KNN Algorithm
- Hierarchical Clustering
- Anomaly Detection
- Neural Networks
- Principle Components Analysis
- Independent Component Analysis
→ Association
- Apriori Algorithm
- Singular Value Decomposition
3.Semi-Supervised Learning:
→ Semi-Supervised Learning have a bit knowledge about data and try to make algorithm and make unlabeled data to labeled.
4.Reinforcement Learning:
→ Reinforcement learning is a form of machine learning method in which a smart agent interacts with its surroundings and learns how to operate in that environment and generally used in gaming.
In next blog, we will discuss more about Types of Supervised Learning..
To Be Continued…
