Sh4kiba

Sh4kiba's Stars

• ramtiin/Attention-Based-LSTM-Network-for-Predicting-Times-Series

  Forex price movement forecast

  Language:Jupyter Notebook338

• ramtiin/Predicting-Stock-Prices-Using-FB-Prophet

  Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. In this notebook I'm going to try forecasting Google stock price using facebook's prophet model.

  Language:Jupyter Notebook152

• ramtiin/Traffic-forecasting-using-different-methods

  Time series prediction using deep learning

  Language:Jupyter Notebook113

• ramtiin/Credit-Card-Fraud-Detection

  In this project, I explore different methods for detecting credit card fraud transactions; including using the Catboost algorithm with undersampling & oversampling methods, and using an almost new approach, by using deep learning and autoencoder.

  Language:Jupyter Notebook7

• ramtiin/Predicting-YouTube-Dislikes-using-Machine-Learning

  I used Catboost for training a model on the numerical features of every YouTube video (e.g., the number of views, comments, likes, etc.) along with sentiment analysis of the video descriptions and comments using the VADER sentiment analysis model.

  Language:Jupyter Notebook9

• ramtiin/Word-Clouds-With-Sentiment-Analysis-of-the-Most-Recent-Tweets

  Downloaded tweets from the most popular news agencies and extract keywords from them. In the next steps, I plotted a word cloud and did a sentiment analysis for tweets that have the keywords.

  Language:Jupyter Notebook5