Deep Learning with Python

Deep learning is part of a broader family of machine learning methods based on artificial neural networks. Learning can be supervised, semi-supervised or unsupervised. Here we have listed some interview questions that can help you to prepare for deep learning with python job role.

Q.1 What is the objective of PYTHONPATH environment variable?
PYTHONPATH has a role similar to PATH. The PYTHONPATH variable tells the Python interpreter where to locate the module files imported into a program. This would include the Python source library directory and the directories containing Python source code. Also the PYTHONPATH is sometimes preset by the Python installer.
Q.2 What method would you use to import a decision tree classifier in sklearn?
In this case we would import a decision tree classifier in sklearn from sklearn.tree import
Q.3 Name the libraries in Python used for Data Analysis and Scientific computations.
the libraries in Python used for Data Analysis and Scientific computations are NumPy, SciPy, Pandas, SciKit, Matplotlib, Seaborn
Q.4 Which library should be preferred for plotting in Python language?
Matplotlib is the python library which has been used for plotting but it requires a lot of fine-tuning to ensure that the plots look shiny. On the other hand seaborn helps data scientists create statistically and aesthetically appealing meaningful plots. Therefore the answer to this question is based on the requirements for plotting data.
Q.5 How can we check if a data set or time series is Random?
In order to check whether a dataset is random or does not use the lag plot when the lag plot for the given dataset does not show any structure then it is random.
Q.6 What is the code to sort an array in NumPy by the nth column?
Using argsort () function this can be achieved. If there is an array X and you would like to sort the nth column then code for this will be x[x [: n-1].argsort ()]
Q.7 How can we copy objects in Python?
Functions used to copy objects in Python are -
1. Copy.copy () for shallow copy
2. Copy.deepcopy () for deep copy

But it is not possible to copy all objects in Python using these functions. Therefore for instance, dictionaries have a separate copy method whereas sequences in Python have to be copied by ‘Slicing’
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