Collect real-time data of the cryptocurrency ETH prices to create a training dataset. Use the Long Short-Term Memory (LSTM) algorithm to train a model that predicts future prices of ETH. Implement a forecast chart interface that updates data in real-time on Django

✅ Collect real-time ETH price data using Coinbase's API

✅ Preprocess the training data using scaling methods and data segmentation

✅ Use the Long Short-Term Memory (LSTM) algorithm to train the model

✅ Implement a WebSocket server to transmit real-time data to the web interface on Django

Trained a facial recognition model using MTCNN, FaceNet, and an SVM Classifier to identify students' faces in the system. Deployed the solution on an IoT device using a Raspberry Pi 4 as the server. The management system updates events in real-time, running entirely on the Raspberry Pi 4.

✅ Detects faces in frames using MTCNN.

✅ Extracts facial features with FaceNet.

✅ Utilizes an SVM Classifier for facial identification.

✅ Implements a WebSocket server to transmit real-time data to a web interface built with Django.

✅ Deployed on an IoT device using a Raspberry Pi 4.

Collect data on products sold on Shopee, then analyze and derive insights from the data. Present the results through visualizations on the interface using Highcharts.js.

✅ Crawl data from home page of Shopee

✅ Data analysis

✅ Data visualization