Tell about your experience applying machine learning methods in projects.

In projects, I have applied machine learning methods to solve classification and regression tasks. For example, I used libraries such as scikit-learn and TensorFlow to build models like logistic regression, random forests, and neural networks. In one project, I implemented a customer churn prediction system, where I trained a model based on historical data to help identify customers at high risk of leaving.

Here's a simple example code using scikit-learn for classification:

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score

# Load data
iris = load_iris()
X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.3, random_state=42)

# Train model
model = RandomForestClassifier(n_estimators=100, random_state=42)
model.fit(X_train, y_train)

# Make predictions and evaluate
predictions = model.predict(X_test)
print(f'Accuracy: {accuracy_score(y_test, predictions):.2f}')