Deep Learning Fundamentals

Neural networks, backpropagation, CNNs, RNNs, and training workflows.

Machine Learning• intermediate

Course overview

3 lessons
1 hr of lessons
Last updated 2024-01-18
W

Webnetis training team

Course trainers

What you'll learn

Understand neural network architectures
Master backpropagation and gradient descent
Build and train CNNs for image recognition
Implement RNNs and LSTMs for sequence data
Deploy deep learning models to production

Course content

3 lessons • 1 hr
1
Neural Networks 101

Perceptrons to multilayer nets.

20 min
2
Convolutional Nets

Vision models and convolutions.

22 min
3
Recurrent Nets

Sequences with RNN/LSTM/GRU.

18 min

Requirements

  • Python programming experience
  • Basic understanding of linear algebra
  • Familiarity with machine learning concepts
  • Access to GPU (optional but recommended)

About this course

This course covers the fundamentals of deep learning with hands-on projects. You'll build neural networks from scratch and learn to use popular frameworks like TensorFlow and PyTorch.

Resources

TensorFlow Setup Guide

link

$149$249
40% OFF

One-time payment

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Certificate of completion
Source code included
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30-day refund guarantee

Full refund within 30 days if you're not satisfied

Course Info

English
1 hr total
3 lessons
Certificate of completion
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