Codanics

Exploratory Data Analysis (EDA) Kyun Zaroori Hai?

Why EDA is important?

Salam, data science dost! Aaj hum guftagu karein gay do bohat ahem topics par jo data science aur machine learning (ML) ke duniya mein har kadam par sath detay hain: EDA (Exploratory Data Analysis) aur data pre-processing.

1. EDA (Exploratory Data Analysis) Ki Importance 🕵️‍♂️

Jab aap kisi naye dataset se milte hain, toh sabse pehla kaam kya hota hai? Bina sochay samjhay ML model train karna? Nahi, yaar! Pehla kaam jo humein karni chahiye, woh hai EDA.

– Data Ko Samajhna: 🧠

– Mushkilat Ko Pehchanna: 🧐

– Data Ki Kahani Sunna: 📖

– Exploratory Data Analysis k liay ye blogs zaroor parhen

2. Data Pre-processing: ML Ke Liye Data Ki Tayyari 🛠️

Agar EDA data ko samajhne ka pehla qadam hai, to data pre-processing woh qadam hai jisse hum data ko machine learning ke liye ready karte hain.

– Data Ki Safai: 🧹

– Data Ko Convert Karna: 🔄

– Feature Engineering: 🔧

3. EDA aur Data Pre-processing: Data Science aur ML Ka Backbone 💪

Conclusion: Data Science Aur ML Ki Safar Ka Saathi 🚗

Agar EDA aur data pre-processing na hoti to? ML projects mein kai challenges aate. Lekin in dono tools ke saath, aap data science aur ML mein behtar tajurba hasil kar sakte hain.

Aakhir mein yaad rahe: Aik Machine Learning model sirf utna hi acha hota hai jitna uska data. EDA aur pre-processing ke zariye, hum is data ko behtar bana sakte hain. Happy coding! 🚀🎉

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