Object Classification Training Framework

Official implementation of the paper: "ZClip: Adaptive Spike Mitigation for LLM Pre-Training".

[Re] Can gradient clipping mitigate label noise? (ML Reproducibility Challenge 2020)

Code for the NeurIPS 2020 paper "Improved analysis of clippind algorithms for non-convex optimization", including various clipping algorithms for neural network training in CV and NLP.

Coursera - RNN Programming Assignment: In this project, we are in charge of a special task: Leading biology researchers are creating new breeds of dinosaurs and bringing them to life on earth, and our job is to give names to these dinosaurs. If a dinosaur does not like its name, it might go berserk, so choose wisely!

Build a Multi-turn Conversations Chit-Chat Bot

Neural network for machine translation using sequence to sequence model on a dataset of English and French sentences

Predicting whether two persons meeting in a speed dating event get matched using deep learning methods

StableStockPredictor is a robust deep learning model for predicting S&P 500 stock prices, built with TensorFlow and Keras. It leverages LSTM networks with gradient clipping, robust scaling, and stable feature engineering (e.g., RSI, moving averages, volatility) to ensure reliable performance in volatile markets.

Text generation from Coursera deeplearning.ai "Sequence Models" course.

Successfully established an LSTM model to effectively forecast global equity based on over 20+ years of historical data of global equity.

Recurrent neural network for building a character-level language model and its application to generating new dinosaur names

Allows automatic gradient norm clipping. This feature can help to stabilize training in certain situations by limiting the magnitude of gradient updates. The implementation is inspired by the paper "AutoClip: Adaptive Gradient Clipping for Source Separation Networks"