This series explains concepts that are fundamental to deep learning and artificial neural networks for beginners. In addition to covering these concepts, we also show how to implement some of the concepts in code using Keras, a neural network API written in Python. We will learn about layers in an artificial neural network, activation functions, backpropagation, convolutional neural networks (CNNs), data augmentation, transfer learning and much more!
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Deep Learning playlist overview & Machine Learning intro
In this video, we introduce what this Deep Learning playlist will cover, and we also explain the concept of machine lear…
1
Deep Learning explained
In this video, we explain the concept of deep learning.
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00:00 Welcome to DEEPLIZARD - Go to d…
2
Artificial Neural Networks explained
In this video, we explain the concept of artificial neural networks and show how to create one (specifically, a multilay…
3
Layers in a Neural Network explained
In this video, we explain the concept of layers in a neural network and show how to create and specify layers in code wi…
4
Activation Functions in a Neural Network explained
In this video, we explain the concept of activation functions in a neural network and show how to specify activation fun…
5
Training a Neural Network explained
In this video, we explain the concept of training an artificial neural network.
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00:00 Welcome…
6
How a Neural Network Learns explained
In this video, we explain the concept of how an artificial neural network “learns” during the training process. We also …
7
Loss in a Neural Network explained
In this video, we explain the concept of loss in an artificial neural network and show how to specify the loss function …
8
Learning Rate in a Neural Network explained
In this video, we explain the concept of the learning rate used during training of an artificial neural network and also…
9
Train, Test, & Validation Sets explained
In this video, we explain the concept of the different data sets used for training and testing an artificial neural netw…
10
Predicting with a Neural Network explained
In this video, we explain the concept of using an artificial neural network to predict on new data. We also show how to …
11
Overfitting in a Neural Network explained
In this video, we explain the concept of overfitting, which may occur during the training process of an artificial neura…
12
Underfitting in a Neural Network explained
In this video, we explain the concept of underfitting during the training process of an artificial neural network. We al…
13
Supervised Learning explained
In this video, we explain the concept of supervised learning. We also show how supervised learning occurs in code with K…
14
Unsupervised Learning explained
In this video, we explain the concept of unsupervised learning. We also discuss applications of unsupervised learning, l…
15
Semi-supervised Learning explained
In this video, we explain the concept of semi-supervised learning. We also discuss how we can apply semi-supervised lear…
16
Data Augmentation explained
In this video, we explain the concept of data augmentation, as it pertains to machine learning and deep learning. We als…
17
One-hot Encoding explained
In this video, we discuss what one-hot encoding is, how this encoding is used in machine learning and artificial neural …
18
Convolutional Neural Networks (CNNs) explained
CNNs for deep learning
Included in Machine Leaning / Deep Learning for Programmers Playlist:
https://www.youtube.com/pla…
19
Convolutions in Deep Learning - Interactive Demo App
In deep learning, convolution operations are the key components used in convolutional neural networks. A convolution ope…
20
Visualizing Convolutional Filters from a CNN
In this video, we learn how to visualize the convolutional filters within the convolutional layers of a CNN using Keras …
21
Zero Padding in Convolutional Neural Networks explained
Let's start out by explaining the motivation for zero padding and then we get into the details about what zero padding a…
22
Max Pooling in Convolutional Neural Networks explained
Let's start by explaining what max pooling is, and we show how it's calculated by looking at some examples. We then disc…
23
Max Pooling in Deep Learning - Interactive Demo App
In deep learning, max pooling is a type of operation that is typically added to convolutional neural networks following …
24
Backpropagation explained | Part 1 - The intuition
Let's discuss backpropagation and what its role is in the training process of a neural network. We're going to start out…
25
Backpropagation explained | Part 2 - The mathematical notation
We covered the intuition behind what backpropagation's role is during the training of an artificial neural network.
htt…
26
Backpropagation explained | Part 3 - Mathematical observations
We have focused on the mathematical notation and definitions that we would be using going forward to show how backpropag…
27
Backpropagation explained | Part 4 - Calculating the gradient
We're now on number 4 in our journey through understanding backpropagation. In our last video, we focused on how we can …
28
Backpropagation explained | Part 5 - What puts the "back" in backprop?
Let's see the math that explains how backpropagation works backwards through a neural network.
We've seen how to calcu…
29
Vanishing & Exploding Gradient explained | A problem resulting from backpropagation
Let's discuss a problem that creeps up time-and-time during the training process of an artificial neural network. This i…
30
Weight Initialization explained | A way to reduce the vanishing gradient problem
Let's talk about how the weights in an artificial neural network are initialized, how this initialization affects the tr…
31
Bias in an Artificial Neural Network explained | How bias impacts training
When reading up on artificial neural networks, you may have come across the term “bias.” It's sometimes just referred to…
32
Learnable Parameters in an Artificial Neural Network explained
Let's talk about learnable parameters within an artificial neural network. These parameters are also referred to as trai…
33
Learnable Parameters in a Convolutional Neural Network (CNN) explained
Here, we're going to learn about the learnable parameters in a convolutional neural network. Last time, we learned about…
34
Regularization in a Neural Network explained
In this video, we explain the concept of regularization in an artificial neural network and also show how to specify reg…
35
Batch Size in a Neural Network explained
In this video, we explain the concept of the batch size used during training of an artificial neural network and also sh…
36
Fine-tuning a Neural Network explained
In this video, we explain the concept of fine-tuning an artificial neural network. Fine-tuning is also known as “transfe…
37
Batch Normalization (“batch norm”) explained
Let's discuss batch normalization, otherwise known as batch norm, and show how it applies to training artificial neural …
