Probability Refresher

A Simple Bayesian Network

Bayesian Network with three random variables. Notice that it is a directed acyclic graph. Each variable can take two values: True or False

What we want to calculate is P(L, R, W).

We can write this probability as P(L) x P(R) x…

What is a primary key?

What is a foreign key?

Get inspired by numbers

Data tells us stories. In statistics, these stories are illustrated with charts, graphs and tables. They illustrate dominance; they reveal change; they help us organize; they educate us; they empower us; the more know, the more curious we become.

Where to begin?

In novelty detection, you have a dataset that contains only good data and you are trying to check if new observations are similar to the the good data. In other words, our goal is to check if new observations are outliers.

In outlier detection, you dataset may already have outliers and your goal is to identify such outliers.

Both novelty detection and outlier detection are used to detect anomalies.

Outlier detection is an unsupervised anomaly detection algorithm.

Novelty detection is a semi-supervised anomaly detection algorithm.

Outlier detection methods available in scikit-learn (LOF does not have a decision boundary as it does not have a predict method when used as an outlier detection algorithm)

(Source: Analytics Vidya)

Answer = 4

You select the y that has the maximum range that does not change the cluster assignment.

Source: Machine Learning Mastery

Adjusting Rows

Adjusting Columns

Adjusting Values

Adjusting Columns + Values

Adjusting Rows + Columns

In deep learning, you don’t have the bias-variance trade off as DL models allow you to reduce both!

A key observation is that in traditional ML, the performance reaches a pleatau after certain amount training data whereas in DL, performance improves with more training data.

Performance of Traditional ML vs. DL models


#probability #statistics #ML #DL #coding #security #building #digest

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