Data Analytics
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Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making.

Admin: @HusseinSheikho || @Hussein_Sheikho
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Numpy_Cheat_Sheet.pdf
4.8 MB
NumPy Cheat Sheet: Data Analysis in Python

This #Python cheat sheet is a quick reference for #NumPy beginners.

Learn more:
https://www.datacamp.com/cheat-sheet/numpy-cheat-sheet-data-analysis-in-python

https://t.me/DataAnalyticsX
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πŸ‘ A fresh deep learning course from MIT is now available publicly

A full-fledged educational course has been published on the university's website: 24 lectures, practical tasks, homework assignments, and a collection of materials for self-study.

The program includes modern neural network architectures, generative models, transformers, inference, and other key topics.

A great opportunity to study deep learning based on the structure of a top university, free of charge and without simplifications β€” let's learn here.
https://ocw.mit.edu/courses/6-7960-deep-learning-fall-2024/resources/lecture-videos/

tags: #python #deeplearning

➑ @codeprogrammer
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Data Science Roadmap.pdf
15.5 MB
🏷 Comprehensive Data Science Roadmap Notes

βœ… This roadmap is exactly the secret recipe you need to get out of confusion and know how to step-by-step prepare yourself for the job market.

πŸ•‘ From mastering Python and SQL to cleaning data and working with cloud tools, which are prerequisites for any project.

πŸ•‘ How to extract real analysis reports and strategies from raw data using statistics and visualization tools.

πŸ•— You will learn everything from machine learning and advanced algorithms to precise model evaluation.

πŸ•™ Get familiar with neural networks, generative artificial intelligence, and language models to have a voice in today's modern world.

πŸ•§ How to build real projects and portfolios that are exactly what hiring managers and big companies are looking for.

🌐 #DataScience #DataScience #pytorch #python #Roadmap

https://t.me/CodeProgrammer
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Pandas vs. Polars: A Complete Comparison of Syntax, Speed, and Memory

Need help choosing the right #Python dataframe library? This article compares #Pandas and #Polars to help you decide.

If you've been working with data in Python, you've almost certainly used pandas. It's been the go-to library for data manipulation for over a decade. But recently, Polars has been gaining serious traction. Polars promises to be faster, more memory-efficient, and more intuitive than pandas. But is it worth learning? And how different is it really?

In this article, we'll compare pandas and Polars side-by-side. You'll see performance benchmarks, and learn the syntax differences. By the end, you'll be able to make an informed decision for your next data project.

Read: https://www.kdnuggets.com/pandas-vs-polars-a-complete-comparison-of-syntax-speed-and-memory

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Machine Learning in python.pdf
1 MB
Machine Learning in Python (Course Notes)

I just went through an amazing resource on #MachineLearning in #Python by 365 Data Science, and I had to share the key takeaways with you!

Here’s what you’ll learn:

πŸ”˜ Linear Regression - The foundation of predictive modeling

πŸ”˜ Logistic Regression - Predicting probabilities and classifications

πŸ”˜ Clustering (K-Means, Hierarchical) - Making sense of unstructured data

πŸ”˜ Overfitting vs. Underfitting - The balancing act every ML engineer must master

πŸ”˜ OLS, R-squared, F-test - Key metrics to evaluate your models

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I found the BEST video explaining how LLMs work πŸ‘‡

πŸ”— check out the full video here : https://lnkd.in/dvjZS89d

#LLM #ML #AI #Python

By: https://t.me/DataAnalyticsX
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LLM Interview Questions.pdf
71.2 KB
πŸ”– 50 interview questions for LLM

A good warm-up before the interview: 50 questions on Large Language Models in one document. Not in-depth, but as a checklist to test your knowledge β€” just perfect.

tags: #LLM #ML #python #pytorch

➑ https://t.me/DataAnalyticsX
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