machine learning(Python)

Write a Python script to generate the best fit model based on your dataset (use any dataset), and apply Support Vector Machine (SVM) / Decision Tree (DT) algorithms.

Then, evaluate the model through various validation methods such as validation or random data testing, metrics, and note your feedback on the results.

Note: The project must contain the following steps and clarify what lines are responsible for each step, for example from line 1 to 3 are responsible for data collection and so on

a) Data collection

b) Data processing

c) Choose a template based on your question

d) Training the model

e) model evaluation

f) Parameter tuning

g) Make a prediction

Project Instructions. 1. Choose the Data set and get instructor approval for validation. 2. Create the best fitting model based on your data set, by applying Support Vector Machine (SVM)/Decision Tree (DT) algorithms. 3. Evaluate the model by different validation methods like cross validation or random data testing, metrics and note your observations of results. 4. Complete information of the algorithm must be given. Note: All Project must contains the following steps a) Data Collection b) Data Preparation c) Choose a model based on your question d) Train the model e) Evaluate the model f) Parameter tuning g) Make Prediction