What is the exactly diffence between Machine Learning and Data Mining ??
Machine Learning and Data Mining are closely related fields, but they differ in their focus and methods.
Here are the main differences between these two fields:
Machine learning:
Machine learning is a subset of artificial intelligence that involves teaching computers to learn from data without being explicitly programmed.
In other words, machine learning algorithms can improve their performance on a task by learning from experience.
Machine learning is used in a wide range of applications, such as image recognition, speech recognition, natural language processing, and predictive analytics.
Data mining:
Data mining is the process of discovering patterns in large datasets using statistical and computational techniques.
Data mining is often used to find correlations and associations between different variables in the data and to identify patterns that can be used for prediction or decision-making.
Data mining can be used in a variety of domains, such as marketing, healthcare, and finance.
If we discuss course point of view :
Machine learning courses typically cover topics such as supervised learning, unsupervised learning, reinforcement learning, decision trees, neural networks, and deep learning.
These courses focus on the algorithms and techniques used to train machine learning models, as well as their applications in areas such as computer vision, natural language processing, and predictive analytics.
Data mining courses typically cover topics such as data preprocessing, association rules, clustering, classification, and outlier detection.
These courses focus on the statistical and computational techniques used to discover patterns in large datasets, as well as their applications in areas such as marketing, healthcare, and finance.
Is Human intelligence still relevant in the time of Artificial Intelligence ??
