Why do we need machine learning in big data analytics?
The increasing volume of data requires efficient and automated ways to analyze it, which machine learning offers.
According to machine learning taxonomy, what are the 3 types of learning?
1- Supervised Learning.
2- Unsupervised Learning.
3- Reinforcement Learning.
What is supervised learning?
A machine learning technique in which the model is trained on a labeled training set.
What are the most popular supervised learning tasks?
1- Regression
2- Classification
What is unsupervised learning?
A machine learning technique in which the model is trained on an unlabeled training set.
What are the most popular unsupervised learning tasks?
1- Clustering
2- Anomaly Detection
3-Dimensionality Reduction
4- Association Rule Learning
What is clustering?
A process of grouping similar data points into clusters without the need to label the data.
What is anomaly detection?
A process of detecting deviations from normal data behavior.
What is dimensionality reduction?
A process of reducing the number of dimensions while retaining as much relevant information as possible without the need of labels.
What is association rule learning?
discovering interesting relationships between variables in large datasets.
What is reinforcement learning?
A machine learning technique in which the agent learns by making decisions and getting a reward if the decision is correct and a penalty if the decision is wrong.
What are the problems caused by high-dimensional data?
It make it difficult for the model to find patterns.
