Neural Networks and deep learning are one of the important topics in the data science field for a long time. Scientist have been experimenting this concepts from the late 80's. However, you can see a huge revolution and industrialization of deep learning concepts in the last decade. From autonomous vehicle to face lock which you are using in your cell phone. So that inspired me to take a course in Neural networks and deep learning. Here I am planning to upload my experiments and journey of learning RNN,CNN and other deep learning concepts along with the basics like updating weights and biases. and also playing with neurons and perceptrons. Very base of the NNDL is neurons and perceptrons.
In the perceptron section you can find some mathematical formulas for perceptrons using logic gate and graphical representation. to understand basic concept of the neron and perceptron you can check out this refrence link: https://towardsdatascience.com/what-the-hell-is-perceptron-626217814f53 this is the article written by Sagar Mehra which will give you better understading of the basic concepts.
Activation forms are really important in the deep learning network, and by just changing the activation parameter you can manipulate the model's accuracy. to understand basic concept of the Activation forms you can check out this refrence link: https://towardsdatascience.com/activation-functions-neural-networks-1cbd9f8d91d6 this is the article written by Sagar Mehra which will give you better understading of the basic concepts.
So far we understand basic concepts of the neural network and deep learnings, now we will move forward with some advanced concepts.
There are some important factors that we should consider which are log likelihood, CrossEntropy, MSE and many more, we will see how we can modify it and test it later which you can see in the homework 3.
This Network is used from Michael's book on NNDL. Modification of the network and testing at the and also you can find a report of all tasks at the end of the file.
This is the online version of Michael's book http://neuralnetworksanddeeplearning.com/chap1.html
I am updating more in two the hyper parameter tuning I think by now your concepts will be stronger about basics of the neural network check the cross entropy folder to review till now.
New folder about hyper parameter tuning.
Addede Testing files for furthure advancement in the model.
Added model testing files in the docs.
Added hand written calculation to understand more about activation forms, layers and other hyper parameters. And how it can improve our model.
Revolution of autonomous cars has boomed in the last 10 years. I have written a survey paper for the same which you can find in the survey paper folder.