What is Data Mining 

Thank you so much, this is the perfect video to help me for my data science presentation😁

Thank you for the informative video. These days a lot of people are using data mining to infiltrate companies and finding out what sort of projects they are working on and more...

Thank you very much... That was a very good explanation....

Thank you 😊

Thank you!!

Thank you

Well explained 👍👏👏

Well useful

Thanks, A question though : at 01:15 3 Disciplines of Data Mining : Statistics AI Machine Learning --- Please explain the diffrence between AI and ML as i don't get the subtility here. Thanks again --------- ChatGPT : In the context of data mining, the distinctions between AI and ML are often nuanced but significant: 1. **Artificial Intelligence (AI)**: - AI encompasses a broader set of techniques and approaches aimed at creating machines that can perform tasks requiring human-like intelligence. - In data mining, AI techniques may include not only machine learning but also other methods such as expert systems, natural language processing, computer vision, and robotics. - AI algorithms can range from rule-based systems to deep learning neural networks, and they are designed to mimic human cognitive functions like reasoning, problem-solving, and perception. - In data mining, AI may involve tasks such as automated decision-making, pattern recognition, anomaly detection, and predictive modeling. 2. **Machine Learning (ML)**: - ML is a subset of AI focused specifically on the development of algorithms and statistical models that enable computers to learn from and make predictions or decisions based on data. - ML algorithms learn from labeled or unlabeled data to identify patterns, relationships, and insights without being explicitly programmed for specific tasks. - In data mining, ML techniques are widely used for tasks such as classification, regression, clustering, association rule mining, and recommendation systems. - ML algorithms can be categorized into supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning, each suited to different types of data and objectives. In summary, while AI encompasses a broader range of techniques and capabilities aimed at mimicking human intelligence, ML is a specific subset of AI focused on developing algorithms that learn from data to perform tasks without explicit programming instructions. In the context of data mining, ML is a key component, but AI may involve a broader set of techniques beyond just machine learning algorithms.

Once I learn the skill of Data Mining... how do I generate money for performing this services ?

T Sing