Top Machine Learning Techniques
Machine learning (ML) is transforming industries by enabling systems to learn from data and make intelligent decisions. With numerous ML techniques available, selecting the right one for a given problem is crucial. This blog explores the top machine learning techniques and how to choose the most suitable one for your needs.
Top Machine Learning Techniques
- Supervised Learning
Supervised learning algorithms use labelled data to train models, making them ideal for classification and regression tasks.
- Examples: Linear Regression, Decision Trees, Support Vector Machines (SVM), Neural Networks.
- Use Cases: Spam detection, medical diagnosis, stock price prediction.
- Unsupervised Learning
Unsupervised learning models analyze unlabeled data to find patterns and structures.
- Examples: K-Means Clustering, Hierarchical Clustering, Principal Component Analysis (PCA), Autoencoders.
- Use Cases: Customer segmentation, anomaly detection, data compression.
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