Welcome to My Data Science World!https://www.kaggle.com/kritsadakruapat
https://huggingface.co/kritsadaK
Project 1: Machine learning without any library:
https://github.com/kkowenn/ManualMachineLearning
Project 2: Manual algorithm cosin similarity:
https://www.kaggle.com/code/kritsadakruapat/cosin
Project 3: The Feature Importance score from a decision tree model:
https://github.com/kkowenn/FastworkAnalysisProject
Project 4: Optimizing Performance Metrics to find the best possible combination of hyperparameters to achieve the highest performance. (before tuning vs after tuning)
https://github.com/kkowenn/DataSciencePortfilo/blob/main/Schooltask(WineQuality)/Wine_Quality.ipynb
Project 5: Comparing Regression Models(Linear Regression model with Random Forest Regression, XGBoost Regression and Neural Network) + Exploratory Data Analysis(EDA)
https://www.kaggle.com/code/kritsadakruapat/comparing-regression-models
Project 6: Fraud detection; tuning and interpreting imbalanced data by using SMOTE, RandomizedSearchCV, SHAP
https://www.kaggle.com/code/kritsadakruapat/imbalanced-tuning-interpretability/notebook
java script plot :
Project 7: Applying model on web, draw digits on a canvas and classify them using a pre-trained convolutional neural network (CNN) model by using the MNIST dataset.
https://github.com/kkowenn/DigitRecognitionWeb
Project 8: Transfer Learning with ResNet-50 & MobileNetV2 and etc.
https://www.kaggle.com/code/kritsadakruapat/simpletransferlearning-resnet50-unsatisfied
https://www.kaggle.com/code/kritsadakruapat/mobilenetv2-image-classification
Project 9: RNN model (Vanilla RNN, LSTM, GRU, and Bidirectional RNN) converted text to numbers, and tried different model types (RNN) to see which performed best.
https://www.kaggle.com/code/kritsadakruapat/rnnmodelcomparison?scriptVersionId=182686891
Project 1: Data Augmentation to Fix Overfitting and improve model:
https://www.kaggle.com/code/kritsadakruapat/cnnchangedatacolor-notjustred
https://github.com/kkowenn/AugmentationForDlibModel
Project 2: using mediapose to detect arm to overlay tattoo filter:
https://huggingface.co/spaces/kritsadaK/TattooPoseOverlay
https://github.com/kkowenn/ComputerVisionProject
Project 3: simple yolov (object detection)
https://github.com/kkowenn/SimpleYolov
Project 4: fall detection capture when detect fall with canny edge detection and skeleton and remove the background
https://github.com/kkowenn/Fall-Detection
Project 5: AfterFall team, Senior Project , Real-Time Anti-spoofing (eye blinking detection) Attendance checking System, using Computer Vision to Robust face recognition model and save log on mongoDB and display by Attendance dashboard webcapp
https://github.com/kkowenn/AfterFall-Face-Recognition-System
Project 1: fundamental Natural Language Processing
https://github.com/kkowenn/basic_nlp
Project 2: simple topic modeling by using nmf
https://www.kaggle.com/code/kritsadakruapat/simpletopicmodelingby-using-nmf
Project 2: simple tweet sentiment classification
https://www.kaggle.com/code/kritsadakruapat/simple-tweet-sentiment-classification
Project 2: Data Augmentation to Fix Overfitting (nlp)
https://github.com/kkowenn/Political-Fake-News-Detector-NLP.git
Project 3: Thai word recommender system by using cosine similarty
https://huggingface.co/spaces/kritsadaK/ThaiSentenceSimilarityApp
Project 4: Quantized LoRA-Tuned Llama
https://github.com/kkowenn/DataSciencePortfolio/blob/main/QuantizedLoRATunedLlama/FlexTuneLLM.ipynb
https://huggingface.co/kritsadaK/UltraInteract-Llama-FT
Project 5: gans-on-themnist-dataset
https://www.kaggle.com/code/kritsadakruapat/gans-on-themnist-dataset
Project 6: A LINE chatbot using Retrieval-Augmented Generation (RAG) with Pinecone and OpenAI GPT for intelligent, real-time responses by python
https://github.com/kkowenn/LINE-RAG-AI-Assistant
Project 1: AirFlowProject1: Weather Data ETL Pipeline Using Docker, Docker Compose, Airflow, PostgreSQL, DagsHub, and Python Libraries:
fetch_data_task → process_data_task → upload_data_task
https://dagshub.com/kkowenn/AirFlowProject1
Project 2: Deployment model on Amazon Bucket(s3):
Machine learning model -> Mlflow -> Amazon Web Services
Project 3: Dogecoin Minutely Prediction:
Data Collection (API binance) & Preprocessing -> Model Training & Experiment Tracking (MLFlow) -> Version Control & Pipeline Management (DVC)
https://dagshub.com/kkowenn/End-to-endDogecoinMinutelyPrediction
Project 4: Thailand PM10 Prediction App (stream lit track Log experiments by mlflow )
url(Open Government Data of Thailand) -> mini ETL -> basic ARIMA model -> streamlit display & choose location to predict-> Experiment Tracking -> Version Control & Pipeline Management (DVC)
https://dagshub.com/kkowenn/OpendatathaiMLflow
https://huggingface.co/spaces/kritsadaK/ThailandPM10PredictionApp2022
Scala Project: Scala workspace designed for data analysis with a simple multi-root, Spark SQL and visualization, featuring sub-projects for SQL-based analysis, various plot examples, and including essential configurations
https://github.com/kkowenn/Basic_Scala_ForBigData
Hadoop Project: A Hadoop MapReduce application for efficiently counting word occurrences in a text file, comprising a driver, a mapper, and a reducer
https://github.com/kkowenn/Simple-Hadoop
R Project: Exploratory data analysis (EDA) for the dataset in R lanaguge. The main goal is to analyze factors influencing student performance by exploring data distributions, identifying patterns, and examining relationships among variables.
https://www.kaggle.com/code/kritsadakruapat/eda-forrlanguage
SparkMLib Project: Personalized Beer SVD Recommendations Using Spark MLlib
https://www.kaggle.com/code/kritsadakruapat/svdbyusingsparkmllib
Visualization tool :
PowerBI: https://github.com/kkowenn/MasterPowerBI
looker studio: https://lookerstudio.google.com/reporting/287f8ccf-c993-4185-bcdd-db1e06d7fc36
Web Scraping with Python Project:
https://github.com/kkowenn/MyScrapingProject
Orange data minning Project: