How to Build Neural Networks in Python
 
This course has been meticulously crafted after months of research to provide learners with a comprehensive understanding of building and training a deep neural network from scratch, even without prior knowledge. Recognizing that many learners may not have the luxury of spending 8 to 9 hours in front of a screen learning the basics, this course offers a swift and efficient learning experience.

Designed to instill 100% confidence in students' ability to construct a neural network using TensorFlow in Python, the course covers essential concepts from the outset. It begins by thoroughly exploring neural networks, tracing their origins and development, and elucidating their basic functioning. Subsequently, learners are guided through setting up their working environment. Finally, the course delves into all the necessary aspects for students to confidently build and train a neural network.

What you'll learn:

- Gain insights into the workings of a neural network
- Understand how to implement machine learning algorithms in Google Colab
- Develop the ability to construct and train deep neural networks using TensorFlow in Python
- Evaluate network performance graphically

Course Components:

- How to Build Neural Networks in Python