assets/quiz.json

[
    {
      "question": "Which machine learning technique is commonly used for weather forecasting due to its ability to handle time series data efficiently?",
      "options": ["Support Vector Machines (SVM)", "Decision Trees", "Random Forests", "Recurrent Neural Networks (RNN)"],
      "answer": "Recurrent Neural Networks (RNN)"
    },
    {
      "question": "What type of weather data is typically used as input for machine learning models in weather forecasting?",
      "options": ["Historical weather data", "Stock market data", "Social media posts", "Traffic congestion data"],
      "answer": "Historical weather data"
    },
    {
      "question": "Which evaluation metric is commonly used to assess the performance of weather forecasting models, particularly for numerical predictions like temperature or precipitation?",
      "options": ["Accuracy", "F1 score", "Mean Absolute Error (MAE)", "Precision"],
      "answer": "Mean Absolute Error (MAE)"
    },
    {
      "question": "In weather forecasting, what is the process of combining predictions from multiple models to improve overall accuracy and performance called?",
      "options": ["Ensemble learning", "Feature engineering", "Gradient boosting", "Reinforcement learning"],
      "answer": "Ensemble learning"
    },
    {
      "question": "Which data visualization technique is often used to display the relationship between weather variables, such as temperature and humidity, over a specific period?",
      "options": ["Bar chart", "Scatter plot", "Pie chart", "Line graph"],
      "answer": "Line graph"
    },
    {
      "question": "What is the primary advantage of using deep learning models, such as Convolutional Neural Networks (CNN), for weather forecasting?",
      "options": ["They require less computational power.", "They don't require historical weather data.", "They can automatically extract relevant features from raw data.", "They are not affected by missing data."],
      "answer": "They can automatically extract relevant features from raw data."
    },
    {
      "question": "Which step of the weather forecasting process involves gathering and processing data from various sources to initialize the models?",
      "options": ["Post-processing", "Model evaluation", "Data assimilation", "Feature selection"],
      "answer": "Data assimilation"
    },
    {
      "question": "Which machine learning algorithm is well-suited for short-term weather predictions, such as the next few hours or days?",
      "options": ["K-Nearest Neighbors (KNN)", "Long Short-Term Memory (LSTM) networks", "Naive Bayes", "Principal Component Analysis (PCA)"],
      "answer": "Long Short-Term Memory (LSTM) networks"
    }
]