Count-Sketch-Optimizers

Deep learning library in plain Numpy.

CS F425 Deep Learning course at BITS Pilani (Goa Campus)

Toy implementations of some popular ML optimizers using Python/JAX

Modified XGBoost implementation from scratch with Numpy using Adam and RSMProp optimizers.

The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.

Learning about Haskell with Variational Autoencoders

Tennis Game play using Multi Agent DDPG - Deep Reinforcement Learning

Here in this system it discloses a log analysis method based on deep learning for an intrusion detection system, which includes the following steps: preprocess the acquired logs of different types in the target system; perform log analysis on the preprocessed logs using a clustering-based method; then, encode the parsed log events into digital feature vectors, use LSTM-based neural network and log collect-based clustering methods to learn the encoded logs to form warning information.

Keras implementation of arXiv 1806.04854

A deep residual auto-encoding approach to colorize images.