Data Mining and Machine Learning
Data mining aims to extract rules from large amounts of data, while machine learning teaches computers how to learn and understand given parameters. Or in other words, data mining is just a research method that can determine a specific result based on the total amount of data collected. Machine learning uses data mining and computational intelligence algorithms to improve decision-making models. Example applications of data mining and machine learning in business use include: Search engines: Adapting search engine results to search behaviour and search user preferences. The job of a data scientist is to examine data to make predictions, and without data mining and machine learning, a data scientist cannot do their job. They must perform data mining to characterize data, and they must integrate machine learning algorithms to make predictions.
Related Conference of Data Mining and Machine Learning
7th International Conference on Artificial Intelligence, Machine Learning and Robotics
10th World Congress on Computer Science, Machine Learning and Big Data
10th International Conference and Expo on Computer Graphics & Animation
Data Mining and Machine Learning Conference Speakers
Recommended Sessions
- Big Data Algorithm
- Big Data Analytics
- Big Data Applications, Challenges and Opportunities
- Big Data in Nursing Research
- Big Data Management
- Big Data Optimization
- Big Data Technologies
- Big Data Tools and Systems
- Cloud computing
- Data Mining and Machine Learning
- Data Mining Tasks, Processes and Analysis
- Data Mining Tools and Software
- Data Privacy and Ethics
- Data Warehousing
- Forecasting from Big Data