Thread by @MalikHassanAR

5 𝙏𝙊𝙋 𝙋𝙮𝙩𝙝𝙤𝙣 𝙇𝙞𝙗𝙧𝙖𝙧𝙞𝙚𝙨 that you should master to become a 𝘿𝙖𝙩𝙖 𝙎𝙘𝙞𝙚𝙣𝙩𝙞𝙨𝙩

A Thread🧵

#pythonkachilla2 #pythonkachilla #pakdatasci #DataScience #MachineLearning #DataVisualization #DataAnalytics

𝙉𝙪𝙢𝙥𝙮 (𝙉𝙪𝙢𝙚𝙧𝙞𝙘𝙖𝙡 𝘾𝙤𝙢𝙥𝙪𝙩𝙖𝙩𝙞𝙤𝙣)
Numpy is used for numerical computations including matrix calculations and multidimensional array operations. Performing numerical computation in Python is time-consuming so we use NumPy for fast computation.

𝙋𝙖𝙣𝙙𝙖𝙨 (𝘿𝙖𝙩𝙖 𝘼𝙣𝙖𝙡𝙮𝙨𝙞𝙨)
In Data Science, when you get the data you have to preprocess it to make it suitable for analysis. Pandas library provides us the tools to manipulate the data and make sense of the data. It is used for data cleaning/wrangling

𝙈𝙖𝙩𝙥𝙡𝙤𝙩𝙡𝙞𝙗 (𝘿𝙖𝙩𝙖 𝙑𝙞𝙨𝙪𝙖𝙡𝙞𝙯𝙖𝙩𝙞𝙤𝙣)
After Data Cleaning, the next step is to visualize it. For that, Matplotlib is the most used python visualization library because of the variety of features it offers to make effective visualization.

𝙎𝙘𝙞𝙠𝙞𝙩-𝙡𝙚𝙖𝙧𝙣 (𝙈𝙖𝙘𝙝𝙞𝙣𝙚 𝙇𝙚𝙖𝙧𝙣𝙞𝙣𝙜)
Scikit-learn is one of the great python libraries that makes applied machine learning easy for the data scientist. It offers a variety of supervised (classification) and unsupervised (clustering) algorithms to use.

𝙆𝙚𝙧𝙖𝙨 (𝘿𝙚𝙚𝙥 𝙇𝙚𝙖𝙧𝙣𝙞𝙣𝙜)
Keras is a popular python library that is used for deep learning tasks. It offers the ability to create your own deep learning models or use pre-trained models on your data for fast computation.

𝙏𝙝𝙖𝙩’𝙨 𝙖 𝙬𝙧𝙖𝙥 !! Thank you for reading
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