Deep Learning

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CIFAR 10 Image Classification

Trained a Deep Convolutional neural network on the CIFAR10 dataset. Achieving 90% accuracy on the testing data.

Technologies Used: Python, Pytorch

Fashion MNIST Image Classification

Trained a Deep Convolutional neural network on the Fashion MNIST dataset.

Technologies Used: Python, Tensorflow

Generating Music for Text

Developed a LSTM model that learns to compose music from Natural language. Worked on ABC Music Notation.

Technologies Used: Python, Pytorch

Seminar on Tensorflow with Deep Learning

Gave a seminar on Deep learning and using Tensorflow for image classification. Slides and exercises are available on the link below.

Technologies Used: Python, Tensorflow, Numpy

Deep Learning Specialization

This course provided me a broad introduction to Deep Learning. It helped me understand the basic terminologies and concepts of Deep Learning which includes Convolutional networks, Recurrent Neural Networks, LSTMs, Optimizers like Adam, SGD, RMSProp, Way to overcome overfitting in the neural networks like Dropout, Batch Normalization, etc. Completed all the 5 courses of the specialization.