What is meant by Machine Learning?
The term "Machine Learning" refers to a subfield of Artificial Intelligence where algorithms and statistical models are developed to enable computers to learn from data. Unlike traditional programming approaches, where specific rules and instructions are provided, machine learning systems improve through experience and data analysis. This allows machines to recognize patterns, make predictions, and make decisions without being explicitly programmed.
Typical software functions in the area of "Machine Learning":
- Data Preprocessing: Cleaning and transforming raw data into a format suitable for model training.
- Model Training: Applying algorithms to training data to create a model that identifies patterns and relationships within the data.
- Model Evaluation: Assessing the performance of the model using test data to verify the accuracy and effectiveness of the model.
- Hyperparameter Tuning: Adjusting the parameters of a model to achieve the best performance.
- Prediction and Classification: Using the trained model to make predictions or categorize data into predefined classes.
- Model Deployment and Integration: Integrating the trained model into existing systems or applications for use in real-world scenarios.
- Monitoring and Maintenance: Continuously monitoring model performance and updating the model to adapt to new data or changing conditions.