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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Here starts the questions 
Step1:  Visualize the data
Using plt.imshow() visualize few images (2 to 5)
Step2:  Well.. Train the model
Do what ever you can to train a classifier that have score above 53% accuracy (in the test set) (Always explain what and why you're doing this or that)
Non-justified answer is like no answer... If you've been through an iterative process, descibe the steps that led you to this answer.
Step3:  Show some quantitative results
Is your model efficient ? What is your classification error, your recall and precision. Describe in a sentense what do these results mean given you dataset.
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Python Code:
# Answer
Explanation: Here starts the questions :
What are the classes ?
In other words, in y_train (or y_test) what does 0, 1, 2.... 9 corresponds to ?
End of explanation
# Answer
Explanation: Visualize the data
Using plt.imshow() visualize few images (2 to 5)
End of explanation
# Answer
Explanation: Well.. Train the model
Do what ever you can to train a classifier that have score above 53% accuracy (in the test set) (Always explain what and why you're doing this or that)
Non-justified answer is like no answer... If you've been through an iterative process, descibe the steps that led you to this answer.
End of explanation
# Answer
Explanation: Show some quantitative results
Is your model efficient ? What is your classification error, your recall and precision. Describe in a sentense what do these results mean given you dataset.
End of explanation
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