sequence-models

Structured state space sequence models

Closed-form Continuous-time Neural Networks

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai

Notes for Deep Learning Specialization Courses led by Andrew Ng.

GeoTorchAI: A Framework for Training and Using Spatiotemporal Deep Learning Models at Scale

Full named-entity (i.e., not tag/token) evaluation metrics based on SemEval’13

BTK Akademi -1 Milyon İstihdam Projesi için Merve Ayyüce Kızrak tarafından Hazırlanmıştır.

A Tensorflow based implicit recommender system

Deep Learning Specialization Course by Coursera. Neural Networks, Deep Learning, Hyper Tuning, Regularization, Optimization, Data Processing, Convolutional NN, Sequence Models are including this Course.

sequential content-based recommendation system

STCN: Stochastic Temporal Convolutional Networks

Sequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.

AWS Last Mile Route Sequence Optimization

Code and pretrained models for the paper: "MatMamba: A Matryoshka State Space Model"

Structured Prediction Helps 3D Human Motion Modelling - ICCV '19

My solutions to Quizzes and Programming Assignments of the specialization.

Contains all course modules, exercises and notes of Deep Learning Specialization by Andrew Ng, and DeepLearning.ai in Coursera

This is all my notebooks, lab solutions, and assignments for the DeepLearning.AI Natural Language Processing Specialization on Coursera.

CREsted is a Python package for training sequence-based deep learning models on scATAC-seq data, for capturing enhancer code and for designing cell type-specific sequences.