Sepehr Asgarian's repositories
Stock-Prediction-
In this project, we aim to enhance the prediction of stock market movements using sentiment analysis and deep learning
Dimensionality-Reduction-Using-Genetic-Algorithms
feature extraction using Genetic Algorithm
English-Persian-Search-Engine
In this project, I implemented a Persian, English search engine that can find the best news related to users' query topics. The dataset is a collection of English and Persian news.
Compiler-Design
My implementation for Compiler Design course's projects (Spring 2020)
ZIGZAG-Game-in-unity
The language used for the development of this project is “C#”. The project file contains Assets such as C# scripts, prefabs, sprite images and animation.
-Rbf-Network-Implementation
Implementation of a RBF network using the FCm (c means) algorithm in order to find the best centers for clustering.
100-nlp-papers
100 Must-Read NLP Papers
Contrastive_Learning_Papers
A list of contrastive Learning papers
awesome-financial-nlp
Researches for Natural Language Processing for Financial Domain
bitcoin
Bitcoin Core integration/staging tree
CIFAR-10-Image-Classification-with-CNN
classify images from the CIFAR-10 dataset
Data-Mining
My implementation for AUT Data mining course's projects (Spring 2020) under supervision of Dr. Ehsan Nazerfard, the course instructor.
fantasy-basketball
Scraping statistics, predicting NBA player performance with neural networks and boosting algorithms, and optimising lineups for Draft Kings with genetic algorithm. Capstone Project for Machine Learning Engineer Nanodegree by Udacity.
jupyter-text2code
A proof-of-concept jupyter extension which converts english queries into relevant python code
magenta
Magenta: Music and Art Generation with Machine Intelligence
MyDataSciencePortfolio
Applying Data Science and Machine Learning to Solve Real World Business Problems
Natural-Language-Processing-In-Tensorflow-Course
This repository contains Excercise Notebooks of Course 3-Natural Language Processing in Tensorflow of Tensorflow
papers
Notes from papers I'm reading, mostly NLP
Predictive-Policing
Forecasting the number of crimes using machine learning
Python-for-Signal-Processing
Notebooks for "Python for Signal Processing" book
python-linkedin
Python interface to the LinkedIn API
python_for_microscopists
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
sepehrasgarian.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.