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A model that performs perfectly on training data might still fail in the real world. In this short video, I explain the difference between Overfitting and Generalization — two key concepts every Mach
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Many times, we use Random Forests for solving a machine learning problem. We just use RandomForestClassifier() and run behind the accuracy of the model. But we don't ask the question How the Rando
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In general, most companies do not have a sudden drop-off in their customers. Instead, they lose them without the customer even knowing about it. In my latest newsletter, I break down: • Customer p
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The majority of tutorials consider Linear Regression as a stepping stone to the "advanced" model categories, and therefore consider it simple. The reality is that Linear Regression is the foundation
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💡 Linear Regression is NOT just a beginner model Most tutorials rush through it. They call it “simple” and move on to complex algorithms. But here’s the secret: Linear Regression teaches you: How
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I am excited to share that I am launching a Machine Learning newsletter- Data Greek Insights! I believe that Machine Learning innovations provide greater value when solving real-world problems. This
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Seaborn is a library for making statistical graphics in Python. It builds on top of matplotlib and integrates closely with pandas data structures. Lets Explore Seaborn briefly through the below cheat
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Pandas are used for data manipulation and Data analysis in Python, an essential library for data science professionals. Most of the operations in Pandas can also be done using SQL and R programming. L
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Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. Almost all the Data Professionals who use python for Data Visualization use Matplotl
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Python Commands for Data Cleaning. Lets explore the common commands used in Data Cleaning #python #datascience #carrerchange #dataanalytics #datascientist #newcareer #datasciencetraining
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Learning Python doesn't mean memorizing each and everything. Its knowing how and where to use the basics. Lets go through the basics !!!! The cheat sheet is perfect for beginners. #python #datasc
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Importing excel using Pandas #codewithme #pandas#pythonprogramming #coding Want to read Excel files in Python? Here’s how to do it in seconds with Pandas! First, install Pandas if you haven’t alre
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About @data_greek

Data Greek is a Instagram growing creator. With 4 followers and 12 posts, data_greek's account shows a follower-to-following ratio of 0.7:1. View all content anonymously on Pictame - no login required.

data_greek's engagement rate sits at 35.42%. That's 608% above what you'd typically see for accounts with 1K-10K followers (average 5%) — a sign of a genuinely connected audience.

Out of the last 12 posts, 25% are videos and 75% are photos. Notably, photos tend to get 2.5x more engagement than videos. Content shows up about every 43 days. Captions lean detailed, averaging 621 characters.

35.42% engagement rate — 608% above average for 1K-10K follower accounts.
25% videos, 75% photos. Photos get 2.5x more engagement here.
Posts about every 43 days.

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data_greek
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@data_greek

Data Greek

Public
Posts
12
Followers
4
Top Hashtags
#datascience#datascientist#MachineLearning#DataScience#python#carrerchange#dataanalytics#newcareer

Explore the most impactful hashtags used in recent posts. These tags highlight the core interests and trending topics that define this profile's digital influence and content strategy.

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Popular Hashtags

#photo#music#viralreels#life#ootd#motivation#friends#fun#like4like#me#makeup#selfie
Following
6
Avg. Likes
1
Avg. Comments
0
Engagement
25.00%

💡Machine Learning, Artificial Intelligence, Python & SQL ✨Help you Navigate Data Science 🧑‍💻Self-taught Aspiring Mach...

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