In this final part, we will test our model.
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This clip is from the chapter "Final Project" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this last section, we will be working on our final...

In this video, we will cover Universal Approximation Theorem.
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This clip is from the chapter "Deep learning: Artificial Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to...

In this video, Sapolsky's theory of human behavioral biology is explored, which claims that every behavior is a product of natural selection and biological processes in the brain. The complexity of understanding human behavior is...

What goes into fruit fly courtship? It might seem like an odd question, but understanding its neural underpinnings – and studying the male-female interactions at the milliscale level -- could help us better understand the complexities of...

This video explains how our body responds to different stimuli through the nervous system. It covers the anatomy and function of nerve cells, nerve fibers, and the different types of neurons that make up the nervous tissue. The video...

This video explains why we need convolution.
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This clip is from the chapter "Deep Neural Network Architecture" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on the deep...

This video explains decision boundary in DNN.
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This clip is from the chapter "Deep Neural Network Overview" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on the overview of...

In this video, you will learn about Hopfield neural network.
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This clip is from the chapter "Neural Network Architectures" of the series "Python for Deep Learning — Build Neural Networks in Python".In this section, we will...

In this video, you will learn how to add the input layer and the first hidden layer.
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This clip is from the chapter "Implementation of ANN in Python" of the series "Python for Deep Learning — Build Neural Networks in...

This video explains about the policy network.<br<br/>/>

This clip is from the chapter "Deep RL DQN" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on deep RL DQN.

This video explains about Perceptron.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN foundation for...

This video demonstrates about the Loss function.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN...

This video explains about the implementation of the gradient step.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section...

This video explains about the implementation of DNN ForwardStep.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses...

This video explains about the DNN Dropout.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN foundation...

This is an exercise solution video on DNN architecture.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the...

This video explains about the DNN architecture.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN...

This is an exercise video that explains why activation function is required.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This...

This is an exercise video on DNN architecture.
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This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN...

This video explains VGG16 which is a convolutional neural network model proposed by K. Simonyan and A. Zisserman from the University of Oxford in the paper "Very Deep Convolutional Networks for Large-Scale Image Recognition". This clip...

In this video, you will learn about layers and DEEP networks.
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This clip is from the chapter "Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will dive deeper...

In this part, we will work on the initialization functions and the feedforward.
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This clip is from the chapter "Final Project" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this last...

In this video, we will cover Perceptron.
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This clip is from the chapter "Deep learning: Artificial Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we...

In this video, we will cover why activation function is required exercise.
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This clip is from the chapter "Deep learning: Artificial Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and...