Mention the difference between Data Mining and Machine learning?
Answer: Machine learning relates with the study, design and development of the algorithms that give computers the capability to learn without being explicitly programmed. While, data mining can be defined as the process in which the unstructured data tries to extract knowledge or unknown interesting patterns. During this process machine, learning algorithms are used.
Learn More :
Machine Learning
- Give a popular application of machine learning that you see on a day-to-day basis?
- What is Genetic Programming?
- In what areas is pattern recognition used?
- What are the advantages of Naive Bayes?
- What is a classifier in machine learning?
- What is the difference between artificial learning and machine learning?
- What is algorithm independent machine learning?
- Explain what is the function of 'Supervised Learning'?
- What is the function of unsupervised learning?
- What is 'Training set' and 'Test set'?
- What is the standard approach to supervised learning?
- What are the three stages to build the hypotheses or model in machine learning?
- What are the different Algorithm techniques in Machine Learning?
- What are the five popular algorithms of Machine Learning?
- What is inductive Machine Learning?
- How can you avoid overfitting?
- Why does overfitting happen?
- What is 'Overfitting' in Machine learning?
- What is Machine Learning?
- Give a derivation of for a single example in batch gradient descent? (Gradient Descent For Linear Regression)
- What is the algorithm for implementing gradient descent for linear regression?
- How does gradient descent converge with a fixed step size alpha?
- Why should we adjust the parameter alpha when using gradient descent?
- Why does gradient descent, regardless of the slope's sign, eventually converge to its minimum value?