Photovoltaic power prediction based on weather data for my bachelor thesis

Comparative Analysis of Techniques for Forecasting Time Series in Financial Markets

We have used Support Vector Regression and Random Forest Regression to predict traffic or congestion.

NTHU EE6550 Machine Learning slides and my code solutions for spring semester 2017.

A research based project which uses steganography and ML/deep learning algorithm to reconstruct the lost audio signals from a corrupted file.

SVR for multidimensional labels

A Python-based ML algorithm for the Gibbs free enegy of various intermediates on single atom catalysts

A python based project to predict the future prices of the top 10 trending cryptocurrencies using ML Algorithms like SVR, Decision Tree and LSTM with an interactive frontend using streamlit. Analysis using PowerBi and has DBMS connectivity.

Hyper-parameter tuning of Time series forecasting models with Mealpy

Predict the compensation base on the position level using the SVR machine learning model.

This script recovers the admin password for the NightOwl F6-series of devices, using a documented master password

Developed the Health insurance cost prediction web application using Python,Pandas,GradientBoostingRegressor,Joblib,Tkinter and Streamlit in which the customer can enter the features value in web app like age,sex,children,smoker(yes/no),region then the model will predict the insurance cost

Machine learning and neural network models for CHI logD prediction based on ¹H and ¹³C NMR spectral data. Supplementary code for the third paper in the "From NMR to AI" series.

This repository presents a time series forecasting model for the stock market using SVR and LSTM to build a model that can predict the appropriate time for trading.

The project Epsilon SVR is built from Scratch with minimum Sk Learn packages. This Epsilon SVR improves the SVR Model.

Here I upload my ML test scripts written in MATLAB or Python

Dash application to simulate various regression models

Data Mining and Machine Learning 2022-2023 CEID Project. The project entails a COVID-19 Dataset including information about each country's statistics regarding COVID-19. Libraries used: sklearn,pandas,tensorflow.

Multiple randomized ANN are being generated that is being taken from user input(total number of ANN) then we have approached one of the nature-inspired-algorithms such as DIFFERENTIAL-EVOLUTION(DE) on a soil-content-dataset to prove that it has better prediction and optimising values other than some well defined algorithms such as SUPPORT-VECTOR…

Stock Price Prediction