Name: Aftab Anjum
Type: User
Company: university of jinan
Bio: I am a researcher and data scientist, my research interests involve natural language processing, Machine learning, and evolutionary algorithm
Location: Lahore
Blog: https://aftabanjum4451.github.io/portfolio-aftab.github.io/
Aftab Anjum's Projects
Abstractive summarisation using Bert as encoder and Transformer Decoder
Pytorch abstractive text summarization
A machine translation system and a locality sensitive hashing table for document search based cosin similarity
The project is about multi classification problem, the data set contained the raw tweets provide by different age group of people. This repository contain the code for pre-processing and applying machine learning techniques to predict sentiments of the user.
The repo contains two Implementation, first Implement linear regression from scratch and secondly designed the linear regression by using PyTorch
Longformer for long document classification
The project is about Named-entity recognition which locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages.
Named Entity Recognition system for analyzing the CORD 19 Research Challenge dataset.
Designed the neural network from scratch with NumPy and Pandas.
Artificial neural networks optimization using particle swarm optimization algorithms.
Neural network optimzation using GA
This is repo contains the implementation of Particle Swarm Optimization (PSO) through Python!
A list of resources on how/why to do a PhD
This is a mini project that I worked on, the project is about a movie recommendation system. The system will be returned the 10 most relevant search results according to the search query.
All the state of the art papers related to the recommendation system
This is a mini project, in which i designed the ROBERTA model with PyTorch for sentiment analysis, and the dataset I used is IMDb-Movie-Review. The data contain raw text and its sentiment.
This is a mini project, in which I designed the model for sentiment analysis, and the dataset I used is: Movie-Review. The data contain raw text and its sentiments.
Spelling autocorrect from scratch with python
Start of the art pre-trained Named entity extraction model
Summarize. is a Streamlit application that performs automatic text summarization using both extractive and abstractive models.