Skip to main content

Python Basics - know about libraries

Python's popularity for data science is largely due to the strength of its core libraries, high productivity for prototyping and building small and reusable systems, and its strength as a general purpose programming language.

 python library

For importing any Python library take the reference from the below code snippet in your notebook-


Some core libraries that we will use in data science are as below-

  1. pandas
  2. NumPy
  3. Scipy
  4. matplotlib

Comments

Post a Comment

Popular posts from this blog

Learn the fastest way to build data apps

Another post starts with you beautiful people! I hope you have enjoyed and learned something new from my previous three posts about machine learning model deployment. In one post we have learned  How to deploy a model as FastAPI?  I n the second post, we have learned  How to deploy a deep learning model as RestAPI ? and in the third post, we have also learned  How to scale your deep learning model API?   If you are following my blog posts, you have seen how easily you have transit yourselves from aspiring to a mature data scientist. In this new post, I am going to share a new framework-  Streamlit which will help you to easily create a beautiful app with Python only. I will show here how had I used the Streamlit framework to create an app for my YOLOv3 custom model. What is Streamlit? Streamlit’s open-source app framework is the easiest way for data scientists and machine learning engineers to create beautiful, performant apps in only a few hours!...
48 comments
Read more

Exploring The File Import

Another post starts with you beautiful people! Today we will explore various file import options in Python which I learned from a great learning site- DataCamp . In order to import data into Python, we should first have an idea of what files are in our working directory. We will learn step by step examples as given below- Importing entire text files- In this exercise, we'll be working with the file mobydick.txt [ download here ] It is a text file that contains the opening sentences of Moby Dick, one of the great American novels! Here you'll get experience opening a text file, printing its contents to the shell and, finally, closing it- # Open a file: file file = open('mobydick.txt', mode='r') # Print it print(file.read()) # Check whether file is closed print(file.closed) # Close file file.close() # Check whether file is closed print(file.closed) Importing text files line by line- For large files, we may not want to print all of th...
9 comments
Read more

Machine Learning-Cross Validation & ROC curve

Another post starts with you beautiful people! Hope you enjoyed my previous post about improving your model performance by  confusion metrix . Today we will continue our performance improvement journey and will learn about Cross Validation (k-fold cross validation) & ROC in Machine Learning. A common practice in data science competitions is to iterate over various models to find a better performing model. However, it becomes difficult to distinguish whether this improvement in score is coming because we are capturing the relationship better or we are just over-fitting the data. To find the right answer of this question, we use cross validation technique. This method helps us to achieve more generalized relationships. What is Cross Validation? Cross Validation is a technique which involves reserving a particular sample of a data set on which we do not train the model. Later, we test the model on this sample before finalizing the model. Here are the steps involved in...
27 comments
Read more