Python
Machine Learning
Deep Learning
Statistics
Potluck
100

an immutable, ordered sequence of elements 

What is a Tuple 

100

An error due to erroneous or overly simplistic assumptions

What is Bias 

100

This function calculates a “weighted sum” of its input, adds a bias and then decides whether a node should be “fired” or not

What is an activation function 

100

An error that occurs when the null hypothesis is true, but is rejected

What is a Type 1 error 

100

This is a parameter whose value is set before the learning process begins

What is a hyperparameter 

200

A variable declared outside a function

What is a Global Variable 

200

An algorithm that takes unlabeled points and gradually learn how to cluster them into groups by computing the mean of the distance between different points.

What is K-means 

200

This algorithm minimizes the cost function in order to minimize an error.

What is gradient descent 

200

This visual shows the 5-number statistical summary pictorially

What is a boxplot 

200

This occurs when a model learns the details and noise in the training data to the degree that it adversely impacts the execution of the model on new information

What is overfitting 

300

This statement allows skipping some part of a loop when some specific condition is met and the control is transferred to the beginning of the loop

What is a Continue statement 

300

A graphical representation of the contrast between the true positive rate and the false positive rate at various thresholds

What is an ROC curve 

300

This technique is used to improve the performance of a network. It revises the error and updates the weights to reduce this error

What is backpropagation

300

If you increase the confidence interval THIS also increases

What is the margin of error

300

This function is used when you need to come up with a range of continuous random variables 

What is a Probability Density Function(PDF)

400

An object which can be traversed though

What is an iterator 

400

The conditional probability for this algorithm is calculated as the pure product of the individual probabilities of components. This implies the absolute independence of features. 

What is Naive Bayes 

400

This activation function gives an output of X if X is positive and zeroes otherwise. It is often used for hidden layers.

What is ReLU 

400

If the BLANK is more than then the BLANK, then we fail to reject the H0


What is the p-value and critical value 

400

The decrease in entropy after a dataset is split on an attribute.

What is information gain 

500

And operator that returns true when 2 operands are true

What is an IS operator 

500

A technique that is used to discourage the complexity of a model. It does this by penalizing the loss function. 

What is regularization 

500

This technique is used to reduce the spatial dimensions of a CNN

What is pooling 

500

A measure that indicates the extent to which two random variables change in cycle

What is Covariance 

500

This is an iterative technique which adjusts the weight of an observation based on the last classification

What is boosting