Open In Colab   Open in Kaggle

Intro#

Install and import feedback gadget#

Hide code cell source 
# @title Install and import feedback gadget

!pip install vibecheck datatops --quiet

from vibecheck import DatatopsContentReviewContainer
def content_review(notebook_section: str):
    return DatatopsContentReviewContainer(
        "",  # No text prompt
        notebook_section,
        {
            "url": "https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab",
            "name": "neuromatch_neuroai",
            "user_key": "wb2cxze8",
        },
    ).render()

feedback_prefix = "W2D4_Intro"

Prerequisites#

For this day, it would be beneficial to have prior experience working with the pytorch modeling package, as the last tutorials are going to be concentrated on defining architecture and training rules using this framework. For Tutorials 4 & 5, you might find yourself more comfortable if you are familiar with the reinforcement learning paradigm and with the Actor-Critic model, in particular. Actually, Tutorial 4 will elaborate on the agent already introduced previously in the last tutorial of Day 2, completing the discussion of meta-learning.

Video#

Intro Video#

Submit your feedback#

Hide code cell source 
# @title Submit your feedback
content_review(f"{feedback_prefix}_intro_video")

Slides#