Setting up deep forecasting environment

Pataasin ang iyong marka sa homework at exams ngayon gamit ang Quizwiz!

Google Colab is a notebook-style environment which provides access to machine learning libraries and computing resources like GPU. True False

True

White noise data show no serial correlations because it is a random sequence of iid values. True False

True

Which of the following is a code editor? Python Anaconda VS Code PyCaret

VS Code

This data transformation technique, involves transforming data by taking the logarithm of the values. Power transformation Log transformation Box-Cox transformation both log and box-cox transformation involve taking log of values

both log and box-cox transformation involve taking log of values

Autocorrelation, also known as ----------- , is a measure of the correlation between a time series and a ------- version of itself. serial correlation - lagged serial correlation - lead auto relation - lagged auto relation - lead

serial correlation - lagged

Time series data can be decomposed into three components: trend - season - remainder trend - cycle- remainder cycle- season - remainder none of the above

trend - season - remainder

What is the primary benefit of using Google Colab over a personal workstation for machine learning tasks? Cost-effective Access to powerful GPUs Automatic software updates All of the above

All of the above

Which of the following is a disadvantage of using a personal workstation for machine learning tasks compared to cloud platforms and Google Colab? Limited access to powerful hardware Limited scalability Higher cost All of the above

All of the above

Which of the following statements is correct with regards to time series patterns? A) Trend is a long term movement in the data, either upwards or downwards . A trend can be linear , meaning that it follows a straight line, or it can be nonlinear , meaning that it follows a more complex curve. B) Seasonal pattern is a regular fluctuation in the data that occurs at a specific time of the year, month or week. C) Cyclic is when the data exhibits peaks and valleys that do not occur at a fixed frequency . Economic conditions and the "business cycle" are typically responsible for these fluctuations. All of them None of them Only A and B Only A and C

All of them

Lag variables are variables that are measured at a future point in time relative to the current time period being studied. True False

False

Which of the following is a web-based interactive development environment? JupyterLab VS code Anaconda TensorFlow

JupyterLab

What is the main difference between Keras and TensorFlow? Keras is a deep learning library, while TensorFlow is a machine learning library TensorFlow is more powerful than Keras Keras is more user-friendly than TensorFlow Both libraries can be used for deep learning

Keras is more user-friendly than TensorFlow

Which of the following forecasting models, is NOT typically used as a benchmark model? Simple mean method Naive method Drift Neural Network

Neural Network

What is the main difference between PyCaret and Scikit Learn for machine learning tasks? PyCaret is written in Python, while scikit-learn is written in R PyCaret is more user-friendly, while scikit-learn requires more knowledge of machine learning concepts PyCaret is more suited for deep learning tasks, while scikit-learn is more suited for traditional machine learning tasks PyCaret is a high-code library, while scikit-learn is a low-code library

PyCaret is more user-friendly, while scikit-learn requires more knowledge of machine learning concepts

The ACF of --------- time series tend to have positive values that slowly decrease as the lags increase. Seasonal Cyclical Trend None of the above

Trend

Anaconda is a distribution of Python and R programming languages which simplify package management with conda environment. True False

True


Kaugnay na mga set ng pag-aaral

factors that affect productivity

View Set

Chapter 13 - Central Nervous System Stimulants and Related Drugs

View Set

Life Insurance Basics L1 (ch. 4)

View Set