General
What type of machine learning involves training models on labeled data to make predictions or classifications?
Supervised learning
This ensemble learning method combines multiple decision trees to make predictions.
Random forest
This statistical measure indicates how spread out the values in a dataset are from the mean.
standard deviation
This type of chart is best for showing the composition of a whole and its parts.
Pie chart
This type of neural network is particularly effective for image recognition tasks.
CNN
This popular algorithm clusters data points into groups based on similarity without prior labeling.
K-means
This optimization algorithm is commonly used to minimize the loss function in neural networks.
Gradient descent
This technique is used to identify and remove observations that are significantly different from other observations in the dataset.
Outlier detection
This type of chart is used to show changes in one or more quantities over time, often with lines connecting data points.
Line Chart
This activation function outputs values between 0 and 1, often used in the output layer for binary classification.
Sigmoid
This measure of central tendency is highly sensitive to outliers in a dataset.
Mean
This technique involves training a model on a subset of data and validating it on the held-out portion.
Cross-validation
his technique is used to identify groups of similar data points within a dataset without prior labeling.
Clustering
This type of chart uses rectangular bars to show comparisons among categories.
Bar chart
This technique randomly turns off neurons during training to prevent overfitting.
Dropout
This term describes data that is collected at regular time intervals.
time-series
This metric measures the harmonic mean of precision and recall in binary classification.
F1-score
This type of analysis is used to understand the relationship between a dependent variable and one or more independent variables.
Regression
This common chart type uses vertical or horizontal bars to compare values across categories.
Bar Chart
This popular deep learning framework was developed by Google and is widely used for building neural networks.
TensorFlow
This phenomenon occurs when a model performs well on training data but poorly on new, unseen data.
overfitting
This algorithm finds the hyperplane that best separates classes in a high-dimensional space.
Support Vector Machine
This statistical phenomenon occurs when a model includes irrelevant predictors, potentially leading to decreased predictive power.
Overfitting
This chart uses dots to show the relationship between two variables.
Scatter Plot
This technique involves training a model on one task and then fine-tuning it on a related task.
Transfer learning