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A Friendly Introduction to Recurrent Neural Networks

Serrano.Academy via YouTube

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Overview

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This course introduces recurrent neural networks using vector and matrix examples to show how sequential inputs and previous outputs support prediction and sequence generation. It also briefly explains random initialization, gradient descent, and error reduction for training an RNN.

Syllabus

A friendly introduction to Recurrent Neural Networks
A friendly introduction to Deep Learning and Neural Networks
Vectors
Perfect Roommate
Simple Neural Network
Simple Recurrent Neural Network
Cooking Schedule
More Complicated RNN
Food
Weather
Add
Merge
Start with random weights
Use Gradient Descent
New Error Function

Taught by

Serrano.Academy

Reviews

5.0 rating, based on 2 Class Central reviews

Start your review of A Friendly Introduction to Recurrent Neural Networks

  • Profile image for Mohd Izuan Ibrahim
    Mohd Izuan Ibrahim @MohdIzuanIbrahim
    This course is an outstanding introduction to RNNs! Luis Serrano’s teaching style is engaging and approachable, breaking down complex concepts into digestible, intuitive explanations. The visuals and analogies make abstract ideas like sequence modeling and backpropagation through time much easier to grasp. The pacing is perfect—neither too slow nor overwhelming—and the practical examples reinforce learning effectively. Even with minimal prior knowledge, I came away with a solid understanding of RNNs, LSTMs, and their applications. The production quality is excellent, and Serrano’s enthusiasm keeps the content lively. Highly recommended for anyone curious about deep learning! A fantastic free resource that rivals paid courses. 10/10!
  • Daniel Ponticelli
    Quick and easy introduction to RNNs. It gives you the very basic so you know what it is about and how they work.
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