RFE BSU organization of data processing labs

1. Lab1 task: As of today, cardiovascular diseases stand as one of the primary causes of mortality globally. Your task involves processing a collected dataset comprising risk factors for cardiovascular diseases, followed by the development of a binary classification algorithm to determine whether an individual has the condition. Use SVM & Decision tree.

2. Lab2 task: Email spam not only wastes users' time but also poses additional threats, such as phishing, extortion through false information, distribution of viral and trojan programs, etc. Your task is to develop a classifier that can distinguish spam emails based on message data analysis. The dataset includes emails labeled as either containing or not containing spam. Use Logistic regression & neural network with LSTM layer.

3. Lab3 The dataset contains data on sales of 5 different products and air temperature on those days. The frequency of observations for different products does not coincide. Choose one time serie, create forecasting model, including statistics models & LSTM model.

4. Lab3_5 Get dataset of Power Consumption. Choose one zone and create forecasting model to predict future power Consumption. Use bouth statistics models and deep learning methods.

5. USDpredict Task: Predicting the future exchange rate of the Belarusian ruble against the dollar. There were 13 models created including statistics models & Deep Learning models. Model fitting present in .ipynb file. To train you're own model train.py was created. To test is predict.py model was created. The last one will use model from train.py and National Bank of the Republic of Belarus data to predict future USD cost. predict.py use Flask as GUI.