What you would learn in The Multilayer Artificial Neural Network Course with Python?
Are you interested in the field of Deep learning? This course is designed ideal for you!
This course was designed to share my expertise and to help you understand complex theories, algorithms, and code libraries in a straightforward method.
I'll guide you step-by-step through the artificial neural network.
The course is enjoyable and thrilling, yet at the same time, we get into the deepest part of our artificial neural network. The course is organized in the following manner:
Section 1 Introduction.
Section 2: Fundamental Neural Network
Section 3: Modelling neural networks
Section 4: Classifying Handwritten digits
There are a variety of tools that we will discuss in this class. The tools we will cover include TensorFlow Back-propagation, feed-forward network, and many more. Many other online courses didn't discuss back-propagation. This is a significant mistake since back-propagation is a vital area. The course does not just teach back-propagation theory but also how to implement it into the actual project. This means you'll have an in-depth understanding of back-propagation. You can impress your potential employer by presenting the project through back-propagation.
Additionally, this course is packed with practical exercises inspired by real-world scenarios. This means that you will not only understand the concepts. However, you'll also have the opportunity to get hands-on experience creating yourself models. Three big projects and a few smaller ones to practice what you've learned in the course. The projects listed below:
Content of the Course:
multilayer neural network
Learn how to make use of NumPy to access Numerical Data
Learn how to use Matplotlib for Python Plotting
Multilayer Perceptron (MLP)
Utilize Neural Networks in practice
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