Learned Classification Problem, Linear Boundaries, Higher Boundaries and Perceptron. Perceptron is pretty amazing it worked same as a Neuron.
Learned Error Function, Log-Loss Error Function and cross entropy. Among these cross entropy is the best way to get prediction. Ipython Notebook for Soft max and cross-Entropy and Perceptron
Learned about gradient Descent and continuous perceptron. Ipython Notebook Gradient Descent
Learned about the Neural Network Architure, Backpropogation, made my first neural network, Regularization and different activation function. The thing about neural network is that it is a combination of linear models and the maths behind every function is beautiful. Ipython Notebook for Student Admissions
Build a neural network using Pytorch. Ipython Notebook for Neural Network
Build Neural Network Architecture and trained the model. Ipython notebook for Neural Network and Training Neural Networks.
Build a simple Neural Network from scratch to detect the type of clothes. I got to know that with very simple model you can also get goot accuracy. Ipython Notebook of Fashion MNIST
Build a simple Neural Network from scratch to detect that the image is of cat or dog. Learned about Inference and Validation and how to save and load a trained model. Also learned how to load image files on pytorch. Ipython Notebook of Dogs vs Cats, Inference and Validation, Loadig Image Data.
Learned how to use pre-trained networks to solved challenging problems in computer vision. Used densenet121 model to train a model to find the difference between a cat and a dog. Ipython Notebook of Transfer Learning.
Build a model to recognise numbers using MLP Classification. IPython Notebook of MLP
Build MLP with validation, learned about local connectivity, filters and the convolutional layer. IPython Notebook of MLP with validation
Created some sobel filters and learned the importance of filters. IPython Notebook of Sobel Filter
Learned how CNN is used for image classification.
Build a 3 conovlution layers CNN model to predict 10 lasses, and learned how image augmentation helps in minimizing overfitting. IPython Notebook of CIFAR CNN, Augmentation
Learned about the style transfer technique using CNN and how gram matrix style transfer works.
Build a style transfer model using VGG19 network. IPython notebook of Style Transfer
Learned about Recurrent Neural Networks from CS231n
Attended the Google Cloud on board event where learned about the big data tools and how to implement real time analytics on Google Cloud. Attended the session on Auto ML and learned about the Vission API and NLP Api by google.
Learned about the Architecture of LSTM.
Learned about GRU from Michael Guerzhoy's post
Learned about time seris predictions. IPython notebook of Simple RNN
Learned the characterwise RNN model.
Building a RNN model to predict novel phrases.
Completed the model. IPython notebook of Char RNN
Build a project on IMDB data.
Working on the final Project.
Work in progress
Finished the project, completed a case study on Time series analysis.