How to Build Neural Networks in Python
The best course to learn to build and train a Deep Neural Network (DNN) using TensorFlow & Python in 90 minutes
What you’ll learn
The students will learn how a neural network works
They will also understand how the code machine learning algorithm in Google Colab
The students will be able to build and train deep neural network using TensforFlow in Python
The learners will be able to evaluate the performance of the network graphically
Description
This course has been specially designed with months of research to help learners to understand how to build and train a deep neural network without any prior knowledge. There are many learners who don’t have 8 to 9 hours of time to spend in front of the monitor learning the basics. Sometimes, we need to learn things as quickly as possible. And this is exactly what this course offers.
This course has been prepared to keep in mind that it should train the students to be 100% confident to build a neural network using TensorFlow in Python. The course starts with a comprehensive definition of Neural networks. Then it walks the learners through the origin and development of Neural networks. After that, it covers the basic working principle of a neural network. In the next lesson, this course guides the students to set up their working environment. Finally, in the last lesson, this course covers everything a student needs to learn to build and train a neural network with confidence.
The course follows the following structure:
1. Definition of Neural Network
2. Origin and Development of Neural Network
3. How Neural Network Works
4. Setting up the Working Environment
5. Building the Neural Network
These five lessons will make anyone comfortable to build and train neural networks using TensorFlow in Python.
The best course to learn to build and train a Deep Neural Network (DNN) using TensorFlow & Python in 90 minutes
What you’ll learn
The students will learn how a neural network works
They will also understand how the code machine learning algorithm in Google Colab
The students will be able to build and train deep neural network using TensforFlow in Python
The learners will be able to evaluate the performance of the network graphically
Description
This course has been specially designed with months of research to help learners to understand how to build and train a deep neural network without any prior knowledge. There are many learners who don’t have 8 to 9 hours of time to spend in front of the monitor learning the basics. Sometimes, we need to learn things as quickly as possible. And this is exactly what this course offers.
This course has been prepared to keep in mind that it should train the students to be 100% confident to build a neural network using TensorFlow in Python. The course starts with a comprehensive definition of Neural networks. Then it walks the learners through the origin and development of Neural networks. After that, it covers the basic working principle of a neural network. In the next lesson, this course guides the students to set up their working environment. Finally, in the last lesson, this course covers everything a student needs to learn to build and train a neural network with confidence.
The course follows the following structure:
1. Definition of Neural Network
2. Origin and Development of Neural Network
3. How Neural Network Works
4. Setting up the Working Environment
5. Building the Neural Network
These five lessons will make anyone comfortable to build and train neural networks using TensorFlow in Python.
