This Repositry contains all the codes to brief introduction towards deep learning.
Data is present at https://drive.google.com/drive/folders/10AWC4KYrj0Cf-wCRmYeknP3jyReE6ysu?usp=sharing
For anyone starting with Deep Learning- a note- Firstly, I did python basics of programming with libraries like numpy, matplotlib, pandas and pyplots. Documentation of these are good resources (Pandas notebook and Chetan_LA1). Then I hopped on to Andrew Ng's course on Machine learning and did it till Logistic Regression and Regularization. Then read blogs from http://neuralnetworksanddeeplearning.com/chap1.html . These are great to give you an introduction. This was further followed with videos from Neural networks: https://www.youtube.com/playlist... These are great for a better conceptual and mathematical understanding. This was followed by implementing a neural network on python using just the basic library of numpy of one layer and n number of neurons. You can find the code at - github.com/chetanchawla/Neural-Networks by the nane Chetan LA2 or ANN for reference. Then I learned the basics of CNN theory using Andrej Karpathy's resources. Then I learned Tensorflow through their official documentation for intro. Also look for a document on Tensorflow Tutorial to go through a basic MNIST tutorial of Tensorflow. This was then accompanied by reading RNNs and LSTMs through Colah's blog and implementing them using Keras. Keras was learnt through the official documentation as well. Tutorials for everything can be found in the above mentioned repo