1. Import the necessary packages import pandas as pd import numpy as np from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.linear_model import LogisticRegression from sklearn.metrics import accuracy_score 2. Load the dataset df = pd.read_csv('tweets_api_data.csv') 3. Split the dataset X = df.drop(['classification'], axis=1) y = df['classification'] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) 4. Preprocess the data sc = StandardScaler() X_train = sc.fit_transform(X_train) X_test = sc.transform(X_test) 5. Train the model model = LogisticRegression() model.fit(X_train, y_train) 6. Test the model y_pred = model.predict(X_test) accuracy = accuracy_score(y_test, y_pred) 7. Evaluate the model print('Model accuracy is: ', accuracy)