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Python for Deep Learning - Build Neural Networks in Python - What is Gradient Descent?
In this video, we will understand what Gradient Descent is. This clip is from the chapter "Gradient Descent Algorithm" of the series "Python for Deep Learning — Build Neural Networks in Python".In this section, we will cover Gradient...
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Python for Deep Learning - Build Neural Networks in Python - How do Artificial Neural Networks Work?
In this video, we will understand how artificial neural networks work. This clip is from the chapter "Summary - Overview of Neural Networks" of the series "Python for Deep Learning — Build Neural Networks in Python".In this section, we...
Packt
Fundamentals of Neural Networks - Linear Regression
This video explains statistical machine learning, where you will start with the linear regression model. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...
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Deep Learning - Deep Neural Network for Beginners Using Python - Final Project Part 5
In this final part, we will test our model. 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 project in...
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Data Science and Machine Learning (Theory and Projects) A to Z - RNN Implementation: Language Modelling Next Word Prediction RNN Architecture
In this video, we will cover language modelling next word prediction RNN architecture. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and...
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Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: Number of Neurons Versus Number of Layers
In this video, we will cover number of neurons versus number of layers. 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...
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Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: Universal Approximation Theorem
In this video, we will cover Universal Approximation Theorem. 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...
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Deep Learning CNN Convolutional Neural Networks with Python - Why Derivatives Solution
This is a solution video on why derivatives. This clip is from the chapter "Gradient Descent in CNNs" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on gradient descent in CNNs.
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Deep Learning CNN Convolutional Neural Networks with Python - Why Convolution
This video explains why we need convolution. 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 neural network...
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Deep Learning CNN Convolutional Neural Networks with Python - Practical Tips
This video showcases some practical tips. This clip is from the chapter "Transfer Learning" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on transfer learning.
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Deep Learning CNN Convolutional Neural Networks with Python - Implementation in NumPy BackwardPass 5
This is fifth of the five-part video on implementation in NumPy BackwardPass. This clip is from the chapter "Gradient Descent in CNNs" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on...
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Python for Deep Learning - Build Neural Networks in Python - Adding the Input Layer and the First Hidden Layer
In this video, you will learn how to add the input layer and the first hidden layer. This clip is from the chapter "Implementation of ANN in Python" of the series "Python for Deep Learning — Build Neural Networks in Python".In this...
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Practical Data Science using Python - Regression Problems
This video explains regression problems. This clip is from the chapter "Machine Learning" of the series "Practical Data Science Using Python".This section explains machine learning.
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Reinforcement Learning and Deep RL Python Theory and Projects - Perceptron
This video explains about Perceptron. 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 deep RL.
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Reinforcement Learning and Deep RL Python Theory and Projects - Initializing the Classes
This video demonstrates the initializing of the classes. 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.
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Reinforcement Learning and Deep RL Python Theory and Projects - DNN Hyperparameters
This video explains about the DNN hyperparameters. 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...
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Reinforcement Learning and Deep RL Python Theory and Projects - DNN ForwardStep Implementation
This video explains about the implementation of DNN ForwardStep. 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...
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Reinforcement Learning and Deep RL Python Theory and Projects - DNN Dropout
This video explains about the DNN Dropout. 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 deep RL.
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Reinforcement Learning and Deep RL Python Theory and Projects - DNN Architecture Exercise Solution
This is an exercise solution video on DNN architecture. 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...
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Reinforcement Learning and Deep RL Python Theory and Projects - DNN Architecture Exercise
This is an exercise video on DNN architecture. 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 deep...
Packt
Fundamentals of Neural Networks - Purpose of Neural Networks
This video explains the purpose of neural networks. 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 learn every...
Packt
Fundamentals of Neural Networks - Backward Propagation Through Time
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. This clip...
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Deep Learning - Deep Neural Network for Beginners Using Python - Weighted Sums
In this video, you will learn about weighted sums. 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 into deep learning.
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Deep Learning - Deep Neural Network for Beginners Using Python - Theory of Perceptron
In this video, we will discuss about the theory of perceptron. This clip is from the chapter "Basics of Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will cover the...