Machine Learning Basics
A type of artificial intelligence that allows computers to learn from data and make predictions or decisions without being explicitly programmed.
What is Machine Learning?
Data that has both input features and corresponding output labels used for training a model.
What is labeled data?
A type of unsupervised learning where the model groups similar items together.
What is clustering?
A series of algorithms that mimic the operations of a human brain to recognize patterns and make decisions.
What is a neural network?
Name an application of machine learning in everyday life.
Email spam filtering.
A collection of structured information, typically organized in rows and columns, used for analysis, research, and model training.
What is a dataset?
A type of supervised learning where the model predicts which category an item belongs to.
What is a classification problem?
K-Means or Hierarchical Clustering.
Name an algorithm used for clustering.
Basic units that process input data and pass the information through the network.
What are neurons in a neural network?
Predicting patient outcomes or diagnosing diseases from the medical images.
How is machine learning used in healthcare?
A mathematical representation of a real-world process that is trained using data to make predictions.
What is a model in Machine Learning?
A type of supervised learning where the model predicts continuous values, like the price of a house.
What is regression in Machine Learning?
Market segmentation, where customers are grouped based on purchasing behavior.
What is a common use case for unsupervised learning?
A function in a neural network that decides whether a neuron should be activated or not.
What is an activation function?
A machine learning system that suggests products, services, or content to users based on their preferences and behavior.
What is a recommendation system?
Supervised learning, unsupervised learning, or reinforcement learning.
Name one type of machine learning.
Decision Tree, Support Vector Machine, or K-Nearest Neighbors.
Give an example of a classification algorithm
A process in unsupervised learning to reduce the number of features in a dataset while retaining its essential information.
What is dimensionality reduction?
A subset of machine learning that uses multi-layered neural networks to analyze various levels of abstraction data.
What is deep learning?
To detect objects, make decisions about driving routes, and control the car's movement.
How is machine learning used in self-driving cars?
Supervised learning uses labeled data to train the model, while unsupervised learning finds patterns in data without labels.
What is the difference between supervised and unsupervised learning.
When a model performs well on training data but poorly on new, unseen data because it learned too much from the training data, including noise.
What does "overfitting" means in a model?
Principal Component Analysis (PCA) or t-SNE
Give an example of a dimensionality reduction technique.
A process used to adjust the weights of the neurons by calculating the gradient of the loss function to improve the model's accuracy.
What is the role of back propagation in training a neural network?
Fraud detection or algorithmic trading.
Name an application of machine learning in finances.