Safwan Shamsir's Projects
Trained over 2,000 BBC News to categorize unseen articles into 5 categories namely Sport, Tech, Business, Entertainment and Politics.
Trained more than 500 data to classify into 2 categories namely Benign and Malignant.
Trained nearly 700 official data provided by Ministry of Health Malaysia to forecast Covid-19 cases.
Trained more than 5000 data to categorize either the patient is positive in the result of Covid-19 or not.
Combination of Crosstabs Generator Version 3 and Chart Generator
Version 3 crosstab generator
Trained over 30,000 data to predict the outcome of the subscription by customer.
Dust detection on solar photovoltaics panel using pre-trained CNN models
Learning repositories for FastAPI
Learning repositories for github actions
Trained more than 300 data to predict the Cardiovascular Disease (CVD)
My answer for INVOKE Data Scientist Coding Assessment
PDF chatbot using Langchain, OpenAI API, HuggingFace embeddings, FAISS and Streamlit
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
Rice grain classifier and quality checking using simple machine learning models, basic CNN models, MobileNetV2, OpenCV package.
Trained over 60,000 IMDB rating to categorize positive and negative review
Trained Random Forest model using R programming language for two problems; regression and classification based on the solar power generation that was compiled by Ph.D. candidate Alexandra Constantin.
All course materials for the Deep Learning with TensorFlow course. (TensorFlow Developer Certificate)