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Courses chevron_right Deep Learning chevron_right Premium

Deep Learning Course

Deep Learning Fundamentals - Premium Edition

Beginner Friendly Intuitive Explanations Mathematically Focused Theory Based

Level: Beginner

Instructor: Mandy

$79.99 $99.99 20% Off - Limited Offer

Course thumbnail for Deep Learning Fundamentals - Premium Edition

What's Included:

39 Video Lectures

378 Lines of Code

Watch Duration: 7.8 Hours

169 Inline Math Snippets

143 Pages of Lecture Notes

43 Inline Code Snippets

Reading Time: 7 Hours

230 Custom Visual Graphics

271 Quiz Questions

Updated and Maintained

Deep Learning Fundamentals.

In this course, we introduce the foundational topics in the field of Deep Learning.

What you'll learn ...

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Understand the relationship between AI, machine learning, and deep learning

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Learn about all of the components that make up an artificial neural network

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Learn all the steps involved with training artificial neural networks

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Conceptualize how fundamental concepts are implemented in code via pseudocode examples

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Gain an understanding for optimization, gradient descent, and backpropagation

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Understand the learnable parameters within an artificial neural network

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Learn about the different categories of datasets in deep learning: training, validation, test

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Understand how to detect problems during the network training process

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Learn techniques to improve network training

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Understand the different categories of learning: supervised, unsupervised, semi-supervised

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Learn how to work with and preprocess image data

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Gain an understanding for all the components in a convolutional neural network (CNN)

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Learn exactly how convolutions work with image data to detect patterns

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Understand problems that can occur during CNN training and potential solutions

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Learn how transfer learning works to transfer knowledge gained by one network to another

Deep Learning Fundamentals Syllabus.

Learn the fundamental concepts and how deep learning models work.

Deep Learning Fundamentals - Premium Edition

$79.99 $99.99 20% Off - Limited Offer

Enrolled

What's Included:

Deep Learning Fundamentals.

What you'll learn ...

Deep Learning Fundamentals Syllabus.

Part 1 - DEEP LEARNING AND ARTIFICIAL NEURAL NETWORKS

Section 1 - Intro to Deep Learning

Lesson #1

Deep Learning Fundamentals Course Intro - Premium Edition

Lesson #2

AI vs. Machine Learning vs. Deep Learning - Relationship Overview

Lesson #3

Deep Learning & Computer Vision - Beginner's Introduction

Section 2 - Artificial Neural Networks

Lesson #4

Perceptrons Explained - Deep Learning

Lesson #5

Intro To Artificial Neural Networks

Lesson #6

Layers in Artificial Neural Networks Explained

Lesson #7

Activation Functions in Artificial Neural Networks Explained

Lesson #8

Loss Functions in Artificial Neural Networks Explained

Lesson #9

Training Artificial Neural Networks Explained

Lesson #10

Batch Size & Epochs in Artificial Neural Networks Explained

Lesson #11

Optimization Algorithms in Artificial Neural Networks Explained

Lesson #12

Learning Rates in Artificial Neural Networks Explained

Lesson #13

Backpropagation Intuition - Neural Network Training Explained

Lesson #14

Bias in Artificial Neural Networks Explained

Lesson #15

Learnable parameters in Artificial Neural Networks Explained

Section 3 - Additional Fundamental topics

Lesson #16

Datasets for Deep Learning - Training, Validation, & Test Sets Explained

Lesson #17

Overfitting Explained - Artificial Neural Networks

Lesson #18

Underfitting Explained - Artificial Neural Networks

Lesson #19

Data Augmentation in Deep Learning Explained

Lesson #20

Regularization in Deep Learning Explained

Lesson #21

Supervised Learning Explained

Lesson #22

Unsupervised Learning Explained

Lesson #23

Semi-supervised Learning Explained

Part 2 - CONVOLUTIONAL NEURAL NETWORKS (CNNS)

Section 1 - Image Data Preprocessing

Lesson #24

Data Labels and One-hot Encodings for Deep Learning Explained

Lesson #25

Image Data Pre-processing for Neural Networks Explained

Lesson #26

Image Data As Neural Network Input Explained - Deep Learning

Section 2 - How CNNs work

Lesson #27

Convolutional Neural Networks (CNNs) Explained

Lesson #28

Convolutions in Deep Learning - Interactive Demo App

Lesson #29

How Convolutional Filters Detect Patterns - CNNs Explained

Lesson #30

Convolutional Layers vs. Fully Connected Layers Explained - Deep Learning

Lesson #31

Zero Padding in Neural Networks Explained

Lesson #32

Max Pooling in Neural Networks Explained

Lesson #33

Max Pooling in Deep Learning - Interactive Demo App