training deep leaning models dataset to our needs within pytorch listing - illustrates loading data into memory using pandas listing - loading data into memory #load data into memory using pandas df pd read_csv("/users/downloads/dataset csv"print("df shape:",df shapedf head(out[df shape( using pandas with jupyter notebooks provides an elegant means to explore data iteratively the preceding output is the result of the df head(commandwhich prints the first five rows of the datasetthe df shape command presents the shape of the dataset as [rows columnsin this datasetwe are provided with the details of bank telemarketing activity the dataset captures the details of the customer targeted and some details about the previous and current marketing callalong with the success outcome deposit customer attributes include agejobmarital status (marital)educationwhether they have defaulted on payments (default)current bank balances (balance)and indicators for housing loan and personal loan campaign attributes include the type of contact (contact)the time of the contact (day/monthand the duration (duration)the number of contacts performed by the agent (campaign)the number of days before the previous contact (pdays)the number of previous contacts (previous)and the previous outcome (poutcome