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Messy data is the tax every analyst pays. Might as well pay it in 60 seconds. 🧹
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Follow @TimeToLearnAI for daily Python → AI/ML progress, code examples, and honest reflections.
What was your biggest win this week? Let’s celebrate small wins together! 🚀
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Free AI & Data Analytics Scholarship Opportunity – Jumpstart 2026
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Harness the power of big data. Master statistical analysis, data mining, and predictive modeling this summer to become a highly sought-after data scientist.
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Data Science Course in Noida: Complete Guide
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Free AI & Data Analytics Scholarship Opportunity – Jumpstart 2026
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Start your journey into AI & Data Analytics today.
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Day 40/60—Understanding Train & Test Split 📊
Today I worked on splitting my dataset into training and testing sets, and the difference between the two scores reminded me why proper validation matters in data science.
#PythonForDataScience #MachineLearning #PublicHealth
Day 39 / 60 — Python for Data Science 📊
This chart compares the actual number of deaths with what the model predicted. The closer the points fall along an upward line, the better the model’s predictions.
#MachineLearning #PythonForDataScience #DataAnalytics #HealthcareAnalytics
Feature Engineering Best Practices A Guide for Data Scientists
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Day 38 / 60 — Python for Data Science 📊🐍
Today I practiced model validation using `train_test_split`.
The model returned an R² score of 0.708, which means it explains about 70% of the relationship between cases and deaths.
#DiAnalyst #PythonForDataScience #machinelearning
If you're also learning, building, or working in tech, I’d be glad to connect.
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Start your journey to becoming a high-demand Data Scientist today.
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Day 37 / 60 — Python for Data Science 📊
Today I focused on feature engineering.
After retraining the model, the R² score remained around 0.80, showing consistent performance even after introducing a new feature (total cases).
#DiAnalyst #PythonForDataScience #DataAnalytics
Mastering Python is the first step toward a successful Data Science career
Follow these 5 smart tips to build strong logic, write efficient code, and work on real-world projects.
Consistency + practice = growth
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Day 36/60—Python for Data Science📊
Built a multiple linear regression model today.
Score: 0.80—meaning the model explains about 80% of the changes in deaths.
Growth continues. 🚀
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Python isn’t just a language - it’s a career toolkit 🚀
From data analysis and machine learning to web apps and game development, Python powers it all.
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