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!...
49 comments
Read more

How to install and compile YOLO v4 with GPU enable settings in Windows 10?

Another post starts with you beautiful people! Last year I had shared a post about  installing and compiling Darknet YOLOv3   in your Windows machine and also how to detect an object using  YOLOv3 with Keras . This year on April' 2020 the fourth generation of YOLO has arrived and since then I was curious to use this as soon as possible. Due to my project (built on YOLOv3 :)) work I could not find a chance to check this latest release. Today I got some relief and successfully able to install and compile YOLOv4 in my machine. In this post I am going to share a single shot way to do the same in your Windows 10 machine. If your machine does not have GPU then you can follow my  previous post  by just replacing YOLOv3 related files with YOLOv4 files. For GPU having Windows machine, follow my steps to avoid any issue while building the Darknet repository. My machine has following configurations: Windows 10 64 bit Intel Core i7 16 GB RAM NVIDIA GeForce G...
46 comments
Read more

How to CORRECTLY convert Darknet/Yolov4 weights to TFLite format?

  Greetings, computer vision practitioners👮! I hope you're all doing well in your projects. Recently, I received a new requirement from a client regarding an object detection solution that had been successfully deployed as a REST API. The solution was seamlessly integrated into both web and mobile applications. However, the client encountered network reliability issues, particularly in rural areas where poor connectivity occasionally caused the solution to fail on mobile devices💔. As we know, network disruptions are a common challenge, but they become critical when they impact business operations. My client sought a robust solution to address this issue, ensuring uninterrupted functionality regardless of network conditions. In this blog post, we will explore how I tackled this challenge and implemented an effective solution💓. The Solution: Enabling Offline Object Detection for Mobile Devices Given that network connectivity issues are beyond our control, the most effective soluti...
12 comments
Read more