Implementing a simple percepron and training it with gradient descent optimizer for linear regression task with out any frameworks such as Keras etc.
The first one is 1.py which is a simple implemtation that you can use it as for learning aspects...
I mean there is a perceptron class which I can use it whenever I want with any training data required...
In the second file named 2.py there is a more practical implemenation using the first one but on the real data.
Here I had a dataset of 200 points of x and y and what I did was training this dataset by a perceptron learning algorithm and see the result.
Actually I had to have a big number of epochs becaue the data was really limited .
At the end I have visualized my results by Matplotlib of python.
I have attached the results in my files...
Now I'm trying to make this better actually