Neural Network with **Three** Lines of Code

In this video, I demonstrate how you can build a neural network using just three lines of code. Many practitioners shy away from neural networks due to the perceived complexity of coding them in frameworks like PyTorch or TensorFlow. However, the method I showcase here is refreshingly simple and accessible!
The code and the data file are available here:
github.com/mshossain/Simple_NN
I'll guide you through using MLPRegressor from scikit-learn to construct a neural network capable of handling regression tasks efficiently. This approach is perfect for those who want to leverage the power of neural networks without diving deep into the intricacies of more complex deep learning libraries.
I'll walk you through a practical example, illustrating how you can apply this method to real-world data to make predictions.
By the end of this video, you'll see that you don't need extensive programming skills to implement effective neural network solutions. You'll also learn some tips on optimizing your model for better performance and how to interpret the results.
Here is the playlist "Neural Network Fundamentals" containing the current video:
• Neural Network Fundame...
Here is my Data Science course playlist:
• Data Science/ML Course
Don't forget to like, comment, and subscribe if you find this tutorial helpful. Your feedback helps us create content that meets your learning needs. Enjoy the journey into the world of neural networks with ease and confidence!
Dr. Shahriar Hossain
computing4all.com

[@tanbir2358]

Excellent video, but it should be complied into a playlist!

[@C4A]

That’s a great idea! I will create a playlist on this topic. I will release a video tomorrow on L1, L2 Regularization. That video will be connected to this one. Thanks for watching and commenting.