Cookie Consent
Hi, this website uses essential cookies to ensure its proper operation and tracking cookies to understand how you interact with it. The latter will be set only after consent.
Read our Privacy Policy

Random Initialization

Random Initialization in machine learning refers to the process of setting the initial values of the weights (parameters) of a neural network randomly. This is a critical step to break symmetry and ensure that the model learns various features during training.

The Role of Random Initialization

Without random initialization, all neurons in a given layer of a neural network would learn the same features during training, rendering additional neurons redundant. Random initialization ensures that neurons start off in different states, allowing for diverse feature learning and more efficient training.

Lakera LLM Security Playbook
Learn how to protect against the most common LLM vulnerabilities

Download this guide to delve into the most common LLM security risks and ways to mitigate them.

Related terms
untouchable mode.
Get started for free.

Lakera Guard protects your LLM applications from cybersecurity risks with a single line of code. Get started in minutes. Become stronger every day.

Join our Slack Community.

Several people are typing about AI/ML security. 
Come join us and 1000+ others in a chat that’s thoroughly SFW.