There are 3 repositories under datapreprocessing topic.
Simple tool to split COCO annotations into train/test datasets.
⚡ GUI for editing LLM vector embeddings. No more blind chunking. Upload content in any file extension, join and split chunks, edit metadata and embedding tokens + remove stop-words and punctuation with one click, add images, and download in .veml to share it with your team.
Roadmap for Data Engineering
Analyzing the HR Criteria of a Company and how they promote their Employees and keep Balance between them using Data Analytics, Data Visualizations, and Machine Learning Models for Classification Purposes.
Wind Power Forecasting Based on Hybrid CEEMDAN-EWT Deep Learning Method
Cereja is a bundle of useful functions we don't want to rewrite and .. just pure fun!
Data Science RoadMap
Utilizes a Convolutional-based Transformer architecture for accurate and efficient PV power forecasting.
Monotonic Optimal Binning algorithm is a statistical approach to transform continuous variables into optimal and monotonic categorical variables.
A helper package for Machine Learning and Deep Learning Algorithms
Predicting whether a person who has applied for a loan in a bank would get his/her loan approved or not using Classification Algorithms in Machine Learning, by looking at some common and useful attributes.
My learnings on different algorithms of Machine Learning with Python .
Data Visualization, EDA , Model Building and Deployment etc..
⚒️ Data preprocessing is the process of transforming raw data into an understandable format. It is also an important step in data mining as we cannot work with raw data. The quality of the data should be checked before applying machine learning or data mining algorithms
Automating the process of Data Preprocessing for Data Science
In this project we try to predict home credit default risk for clients. We try to predict, if the client will have payment difficulties or not.
Image Classification model for detecting and classifying *DIABETIC RETINOPATHY* using retina images
Python编写的处理法务邮单自动批量生成的脚本小工具-提取判决书内容免去手输填充邮单-Legal agency postal receipt automatically generate app
The project provides a real-world dataset focusing on supply chain analytics
Resume Screening using Machine Learning and Python
This repository focuses on two machine learning projects in the healthcare domain.
All my Machine Learning Projects from A to Z in (Python & R)
Power BI exercises for courses on DataCamp's Data Analyst in Power BI Career Track
Preparing Mammography Images for the ResNet Algorithm and Performing Data Preprocessing for the Teknofest 2022 Healthcare Artificial Intelligence Competition.
Engineered an innovative project for epilepsy disorder classification by harnessing EEG signals, attaining an outstanding accuracy rate of 95% in identifying diverse seizure types. Implemented sophisticated signal processing techniques and advanced machine learning algorithms, enhancing the system's precision and efficiency in classification.
[Advanced Regression] Predicting the Poverty Probability Index using socioeconomic data from 12600 individuals over 7 African countries
Named Entity Extraction with OpenCV, Pytesseract, Spacy (OCR + NER), BIO Labelling
The aim of this project is to create a custom dataset for sentiment analysis. Use the data to fine-tune a BERT model and deploy your NLP model as an API
Material for Data Mining Lab Session (Fall Semester @ NTHU)
Web Based Exploratory Data Analysis platform. Can be used as a precursor to the Data Preperation/ Preprocessing stage to understand the data through visualizations
Heart disease is a major global health concern that affects millions of people around the world. Early detection and accurate prediction of heart disease can help to prevent the progression of the disease and save lives. In this project, we aim to develop a predictive model for heart disease using various machine learning algorithms.
LGBM and logistic regression for prediction of customers' second time transaction for an online market app.
In this comprehensive machine learning project, I executed the entire machine learning life cycle. Designed a streamlined and visually appealing interface using Streamlit. Ensuring a user-friendly experience for individuals to input their relevant information effortlessly. Handed off well-documented and easily modifiable code.