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jotei02's Projects

airbnbpriceprediction

Training and Testing a Set of Machine Learning/Deep Learning Models to Predict Airbnb Prices for NYC

algo-trading-math-models

Math Techniques viz. ARIMA, Frequency Decomposition, Fourier Filtering, Linear Regression & Bi-directional LSTMs on Feature Engineered Stock Market Data.

credit-card-fraud-detection-using-logistic-regression

Classifying whether the credit card transaction is fraudulent or not using Logistic Regression

credit-card-fraud-detection-using-support-vector-machine

Classifying whether the credit card transaction is fraudulent or not using Support Vector Machines

cv-sudoku-solver

Sudoku solver using computer vision and deep learning to extract and interpret Sudoku puzzles from images. Includes a fully functional Sudoku game built using Pygame.

face-recognition

Machine Learning project to recognise faces from an Image just like facebook or video stream

jse-stock-market-returns-prediction-using-multivariate-time-series-data

An application of Multilayer Perceptron, Random Forest Regression and Recurrent Neural Networks (LSTM)

laplaciansmoothing-gradientdescent

The code for the paper: https://arxiv.org/abs/1806.06317

learning_to_beat_the_random_walk

In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Sentiment Analysis in an effort to predict the directional changes in exchange rates for a list of developed and developing countries.

logistic-regression-dimensionality-reduction

Using the principal component analysis to find the two main features to represent the 13 various wine characteristics and develop a logistic regression model to predict the customer types using the two features as the inputs.

lstm-fcn

Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification

mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

multiridge

Regularisation Optimization

pca-svm-features-based-face-images-classification

Face recognition on The Database of Faces at a glance. Data pre-processing. Dimension reduction using PCA. Support Vector Machines (For classification)

product-sales-forecasting

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

quantitative-trading-project

This project combines logistic regression, gradient boosting, and LSTMs to predict next-month returns.

sentiment-classification

Neural sentiment classification of text using the Stanford Sentiment Treebank (SST-2) movie reviews dataset, logistic regression, naive bayes, continuous bag of words, and multiple CNN variants.

sp500-stock-similarity-time-series

Improve S&P 500 stock price prediction (random forest and gradient boosting trees) with time series similarity measurements: DTW, SAX, co-integration, Euclidean and Pearson.

stocktwits-svm-nlp

This project uses Support Vector Machine and BERT word embeddings to make sentiment prediction on messages from stockttwits, one of the biggest financial forum in the world.

text-classification-and-summarization

Built Logistic regression, SVM, Naive Bayes, RandomForest, KNN for text classification on scrapped news data. Built Text rank, LDA and K-means clustering for text summarization.

time-series-analysis-on-transportation-data

Exploratory Data Analysis of Time Series Data and Forecasting using Naïve Approach, Moving Average Method, Simple Exponential Smoothening, Holt’s Linear Trend Model, Holt’s Winter Model, ARIMA and SARIMAX models.

time-series-arima-xgboost-rnn

Time series forecasting for individual household power prediction: ARIMA, xgboost, RNN

time-series-demand-forecasting

Time-series demand forecasting is constructed by using LSTM, GRU, LSTM with seq2seq architecture, and prophet models.

time-series-forecasting-keras

time series forecasting using keras, inlcuding LSTM,RNN,MLP,GRU,SVR and multi-lag training and forecasting method, ICONIP2017 paper.

time-series-prophet

Time Series Analysis & Forecasting of Rossmann Sales with Python. EDA, TSA and seasonal decomposition, Forecasting with Prophet and XGboost modeling for regression.

time_series_forecasting_pytorch

time series forecasting using pytorch，including ANN,RNN,LSTM,GRU and TSR-RNN，experimental code

twitter-sentiment-analysis

Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc.

twitter-sentiment-analysis-

This is a project of twitter sentiment analysis using machine learning(Support Vector Machines,Naive Bayes), deep learning(LSTM), Transformer(BERT,ROBERTA).

twitter-sentimental-analysis

Sentiment Analysis Twitter

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