If you grew up in the United States, you probably learned the United States Customary System (USCS) for weights and measures. USCS terms like inches, feet, pounds, and miles are derived from the British Imperial System, steeped in a...

In this video, we will work on shapes in RNN.
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This clip is from the chapter "Recurrent Neural Networks (RNNs), Time Series, and Sequence Data" of the series "Deep Learning - Recurrent Neural Networks with TensorFlow".In this...

In this video, you will learn the computation of returns in pairs trading and explore other optional extensions to enhance our pairs trading strategy with ChatGPT, incorporating transaction costs, slippage, risk management techniques,...

In this video, we will explore advanced techniques for computing and evaluating the performance of our pairs trading strategy, including risk-adjusted performance metrics, portfolio optimization, and other sophisticated methods for...

Backpropagation through time (BPTT) is a gradient-based technique for training certain types of recurrent neural networks. It can be used to train Elman networks. The algorithm was independently derived by numerous researchers.
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This video explains the purpose of neural networks.
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This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains artificial neural networks where you will...

This video explains statistical machine learning, where you will start with the linear regression model.
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This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section...

In this video, we will understand why a random variable is important.<br<br/>/>

This clip is from the chapter "Basic Probability" of the series "Deep Learning - Crash Course 2023".In this section, we will talk about probability.

In this video, we will understand how update rule works.<br<br/>/>

This clip is from the chapter "Perceptron" of the series "Deep Learning - Crash Course 2023".In this section, you will learn about Perceptron.

In this video, you will learn about the loss function and parameter update.<br<br/>/>

This clip is from the chapter "Perceptron" of the series "Deep Learning - Crash Course 2023".In this section, you will learn about Perceptron.

In this video, you will learn more about the Perceptron model and understand its representation.
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This clip is from the chapter "Perceptron" of the series "Deep Learning - Crash Course 2023".In this section, you will learn...

In this video, you will learn about the MP Neuron model, also called McCulloch Pitts model.
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This clip is from the chapter "MP Neuron Model" of the series "Deep Learning - Crash Course 2023".In this section, you will learn how...

In this video, we will be introduced to Sigmoid Neuron.<br<br/>/>

This clip is from the chapter "Sigmoid Neuron" of the series "Deep Learning - Crash Course 2023".In this section, we will begin our journey with Sigmoid Neuron.

In this video, we will have a quick recap of Perceptron limitations and learn how Sigmoid Neuron is useful.
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This clip is from the chapter "Sigmoid Neuron" of the series "Deep Learning - Crash Course 2023".In this section, we...

In this video, you will learn about bias in neural networks.
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This clip is from the chapter "Getting the Basics Right" of the series "Deep Learning - Crash Course 2023".In this section, you will learn some basic terms used in...

In this video, you will learn how to apply an activation function to the weighted average to make sure the output value falls between 0 and 1.
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This clip is from the chapter "Getting the Basics Right" of the series "Deep...

In this video, you will learn about artificial neural networks.
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This clip is from the chapter "Getting the Basics Right" of the series "Deep Learning - Crash Course 2023".In this section, you will learn some basic terms used...

In this lesson, we will see our particle system come to fruition as we make use of weight painting to control the placement of the flowers.
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This clip is from the chapter "Using Blender Particle Emitter to Create Foliage" of...

In this video, we will understand the geometrical picture by understanding why neural networks are so important instead of a single neural network.
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This clip is from the chapter "Feedforward Artificial Neural Networks" of the...

In this video, you will learn how to build your first neural network.
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This clip is from the chapter "Creating Deep Neural Networks in PyTorch" of the series "Deep Learning - Computer Vision for Beginners Using PyTorch".In...

In this video, we will dive into action and look at codes for transfer learning with data augmentation.
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This clip is from the chapter "Transfer Learning for Computer Vision" of the series "Deep Learning - Convolutional Neural...

In this video, we will understand convolution on color images.
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This clip is from the chapter "Convolutional Neural Networks (CNNs)" of the series "Deep Learning - Convolutional Neural Networks with TensorFlow".In this...

In this video, you will learn how to view convolution as matrix multiplication.
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This clip is from the chapter "Convolutional Neural Networks (CNNs)" of the series "Deep Learning - Convolutional Neural Networks with...

In this video, we will discuss the two approaches used for transfer learning, which we will use in the next videos.
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This clip is from the chapter "Transfer Learning for Computer Vision" of the series "Deep Learning -...