The requirements for the virtual machine include the need for GPU processing and the use of a PostgreSQL database. While the Data Science Virtual Machine (DSVM) Windows edition does support GPU processing, it does not natively support PostgreSQL, which is typically more associated with Linux environments. Therefore, the requirements will not be fully satisfied with the DSVM Windows edition, making it necessary to use an alternative, such as the DSVM Linux edition.
To design a deep learning model that recognizes language using the most recent edition of Python, TensorFlow is a suitable choice. TensorFlow is an open-source library developed by the Google Brain team, designed specifically for numerical computation and large-scale machine learning. It leverages Python for constructing deep learning models and supports a variety of complex applications, including natural language processing (NLP). Thus, it aligns well with the task of designing a deep learning model for language recognition.
To satisfy the requirements in the context of k-fold cross-validation, it is typical to use k=5 or k=10 as these values are standard and provide a good balance between bias and variance. Using k=3 is less common and may not be sufficient for reliable model evaluation, especially in scenarios where more comprehensive validation is needed. Therefore, configuring k=3 is not considered a usual choice and is likely to not meet the typical requirements.