PyTorch for Deep Learning with Python Bootcamp | 32 | Bringing Backpropagation and ANN Together

PyTorch for Deep Learning with Python Bootcamp | 32 | Bringing Backpropagation and ANN Together

Welcome to the best online course for learning about Deep Learning with Python and PyTorch!

PyTorch is an open source deep learning platform that provides a seamless path from research prototyping to production deployment. It is rapidly becoming one of the most popular deep learning frameworks for Python. Deep integration into Python allows popular libraries and packages to be used for easily writing neural network layers in Python. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more.

This course focuses on balancing important theory concepts with practical hands-on exercises and projects that let you learn how to apply the concepts in the course to your own data sets! When you enroll in this course you will get access to carefully laid out notebooks that explain concepts in an easy to understand manner, including both code and explanations side by side. You will also get access to our slides that explain theory through easy to understand visualizations.

In this course we will teach you everything you need to know to get started with Deep Learning with Pytorch, including:

NumPy
Pandas
Machine Learning Theory
Test/Train/Validation Data Splits
Model Evaluation - Regression and Classification Tasks
Unsupervised Learning Tasks
Tensors with PyTorch
Neural Network Theory
Perceptrons
Networks
Activation Functions
Cost/Loss Functions
Backpropagation
Gradients
Artificial Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
and much more!

By the end of this course you will be able to create a wide variety of deep learning models to solve your own problems with your own data sets.

So what are you waiting for? Enroll today and experience the true capabilities of Deep Learning with PyTorch! I'll see you inside the course!

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introduction to artificial neural networks and deep learning,
introduction to artificial neural networks,
artificial neural network,
introduction to ann,
artificial neural network used for,
application of ann,
artificial neural network algorithm,
artificial neural network theory,
How do I create a neural network in PyTorch?,
What is Backpropagation and how does it work?

What is Backpropagation with example?

What is Backpropagation in machine learning?

What is back-propagation in AI?

How is backpropagation calculated?

Why do we use backpropagation?

What is the time complexity of backpropagation algorithm?

What are general limitations of backpropagation rule?

What is Backpropagation Sanfoundry?

What are the five steps in the backpropagation learning algorithm?

What is Delta in backpropagation?

What is an activation value?

Is backpropagation still used?

How do you implement backpropagation in Python?

What is the objective of backpropagation algorithm?

What can I build with PyTorch?,

How do you use ReLU in PyTorch?,

How do I make a PyTorch model?,

Is PyTorch better than TensorFlow?,

What is Self in PyTorch?,

Is PyTorch easier than TensorFlow?,

Who uses PyTorch?,

How do you predict using PyTorch?,

What is ReLU inplace?,

What is ReLU in machine learning?,

What is inplace in Pytorch?
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