Telegram Web
Polars.pdf
391.5 KB
๐Ÿ“– A comprehensive cheat sheet for working with Polars


๐ŸŒŸ Have you ever worked with pandas and thought that was the fastest way? I thought the same thing until I worked with Polars.

โœ๏ธ This cheat sheet explains everything about Polars in a concise and simple way. Not just theory! But also a bunch of real examples, practical experience, and projects that will really help you in the real world.

โ”Œ ๐Ÿปโ€โ„๏ธ Polars Cheat Sheet
โ”œ โ™พ๏ธ Google Colab
โ”” ๐Ÿ“– Doc

#Polars #DataEngineering #PythonLibraries #PandasAlternative #PolarsCheatSheet #DataScienceTools #FastDataProcessing #GoogleColab #DataAnalysis #PythonForDataScience
๏ปฟ
โœ‰๏ธ Our Telegram channels: https://www.tgoop.com/addlist/0f6vfFbEMdAwODBk

๐Ÿ“ฑ Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Please open Telegram to view this post
VIEW IN TELEGRAM
โค8๐Ÿ‘1
Please open Telegram to view this post
VIEW IN TELEGRAM
โค3๐Ÿ”ฅ2
This channels is for Programmers, Coders, Software Engineers.

0๏ธโƒฃ Python
1๏ธโƒฃ Data Science
2๏ธโƒฃ Machine Learning
3๏ธโƒฃ Data Visualization
4๏ธโƒฃ Artificial Intelligence
5๏ธโƒฃ Data Analysis
6๏ธโƒฃ Statistics
7๏ธโƒฃ Deep Learning
8๏ธโƒฃ programming Languages

โœ… https://www.tgoop.com/addlist/8_rRW2scgfRhOTc0

โœ… https://www.tgoop.com/Codeprogrammer
Please open Telegram to view this post
VIEW IN TELEGRAM
โค2
๐Ÿฅ‡ 40+ Real and Free Data Science Projects

๐Ÿ‘จ๐Ÿปโ€๐Ÿ’ป Real learning means implementing ideas and building prototypes. It's time to skip the repetitive training and get straight to real data science projects!

๐Ÿ”† With the DataSimple.education website, you can access 40+ data science projects with Python completely free ! From data analysis and machine learning to deep learning and AI.

โœ๏ธ There are no beginner projects here; you work with real datasets. Each project is well thought out and guides you step by step. For example, you can build a stock forecasting model, analyze customer behavior, or even study the impact of major global events on your data.

โ”Œ๐Ÿณ๏ธโ€๐ŸŒˆ 40+ Python Data Science Projects
โ”” ๐ŸŒŽ Website

#DataScience #PythonProjects #MachineLearning #DeepLearning #AIProjects #RealWorldData #OpenSource #DataAnalysis #ProjectBasedLearning #LearnByBuilding


โœ‰๏ธ Our Telegram channels: https://www.tgoop.com/addlist/0f6vfFbEMdAwODBk

๐Ÿ“ฑ Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Please open Telegram to view this post
VIEW IN TELEGRAM
โค7๐Ÿ‘1
๐ŸLooking to get started with Deep Learning using PyTorch?

This well-structured GitHub repository is a goldmine for beginners who want to learn PyTorch with hands-on examples and clear explanations๐Ÿ“–.

๐Ÿ—‚ Whatโ€™s Inside?
๐Ÿˆ‚ Jupyter Notebooks with interactive code.
๐Ÿง  Step-by-step tutorials on Tensors, Autograd, and Neural Networks.
๐Ÿ–ผ Real-world mini-projects like image classification.
โŒ› Practical guides on using GPU with PyTorch.
โœ… Beginner-friendly but also great for revision.


๐Ÿ’กIf you're serious about learning AI, this is one of the best free resources to kick off your journey๐Ÿค.

๐Ÿ–ฅ GitHub

โœˆ๏ธ Our Telegram channelsโฌ…๏ธ

๐Ÿ“ฑ Our WhatsApp channelโฌ…๏ธ
Please open Telegram to view this post
VIEW IN TELEGRAM
โค10
๐Ÿ™๐Ÿ’ธ 500$ FOR THE FIRST 500 WHO JOIN THE CHANNEL! ๐Ÿ™๐Ÿ’ธ

Join our channel today for free! Tomorrow it will cost 500$!

https://www.tgoop.com/+Y4vkzbTTshVhYTQ1

You can join at this link! ๐Ÿ‘†๐Ÿ‘‡

https://www.tgoop.com/+Y4vkzbTTshVhYTQ1
โค1
๐—ฌ๐—ผ๐˜‚๐—ฟ_๐——๐—ฎ๐˜๐—ฎ_๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ_๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„_๐—ฆ๐˜๐˜‚๐—ฑ๐˜†_๐—ฃ๐—น๐—ฎ๐—ป.pdf
7.7 MB
1. Master the fundamentals of Statistics

Understand probability, distributions, and hypothesis testing

Differentiate between descriptive vs inferential statistics

Learn various sampling techniques

2. Get hands-on with Python & SQL

Work with data structures, pandas, numpy, and matplotlib

Practice writing optimized SQL queries

Master joins, filters, groupings, and window functions

3. Build real-world projects

Construct end-to-end data pipelines

Develop predictive models with machine learning

Create business-focused dashboards

4. Practice case study interviews

Learn to break down ambiguous business problems

Ask clarifying questions to gather requirements

Think aloud and structure your answers logically

5. Mock interviews with feedback

Use platforms like Pramp or connect with peers

Record and review your answers for improvement

Gather feedback on your explanation and presence

6. Revise machine learning concepts

Understand supervised vs unsupervised learning

Grasp overfitting, underfitting, and bias-variance tradeoff

Know how to evaluate models (precision, recall, F1-score, AUC, etc.)

7. Brush up on system design (if applicable)

Learn how to design scalable data pipelines

Compare real-time vs batch processing

Familiarize with tools: Apache Spark, Kafka, Airflow

8. Strengthen storytelling with data

Apply the STAR method in behavioral questions

Simplify complex technical topics

Emphasize business impact and insight-driven decisions

9. Customize your resume and portfolio

Tailor your resume for each job role

Include links to projects or GitHub profiles

Match your skills to job descriptions

10. Stay consistent and track progress

Set clear weekly goals

Monitor covered topics and completed tasks

Reflect regularly and adapt your plan as needed


#DataScience #InterviewPrep #MLInterviews #DataEngineering #SQL #Python #Statistics #MachineLearning #DataStorytelling #SystemDesign #CareerGrowth #DataScienceRoadmap #PortfolioBuilding #MockInterviews #JobHuntingTips


โœ‰๏ธ Our Telegram channels: https://www.tgoop.com/addlist/0f6vfFbEMdAwODBk

๐Ÿ“ฑ Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Please open Telegram to view this post
VIEW IN TELEGRAM
โค6๐Ÿ‘4
โ—๏ธ WITH JAY MO YOU WILL START EARNING MONEY

Jay will leave a link with free entry to a channel that draws money every day. Each subscriber gets between $100 and $5,000.

๐Ÿ‘‰๐ŸปCLICK HERE TO JOIN THE CHANNEL ๐Ÿ‘ˆ๐Ÿป
๐Ÿ‘‰๐ŸปCLICK HERE TO JOIN THE CHANNEL!๐Ÿ‘ˆ๐Ÿป
๐Ÿ‘‰๐ŸปCLICK HERE TO JOIN THE CHANNEL ๐Ÿ‘ˆ๐Ÿป

๐ŸšจFREE FOR THE FIRST 500 SUBSCRIBERS ONLY!
โค1
Intent | AI-Enhanced Telegram
๐ŸŒ Supports real-time translation in 86 languages
๐Ÿ’ฌ Simply swipe up during chat to let AI automatically generate contextual replies
๐ŸŽ™ Instant AI enhanced voice-to-text conversion
๐Ÿง  Built-in mainstream models including GPT-4o, Claude 3.7, Gemini 2, Deepseek, etc., activated with one click
๐ŸŽ Currently offering generous free AI credits
๐Ÿ“ฑ Supports Android & iOS systems
๐Ÿ”Ž Website | ๐Ÿ“ฌ Download
๐Ÿš€ FREE IT Study Kits for 2025 โ€” Grab Yours Now!

Just found these zero-cost resources from SPOTO๐Ÿ‘‡
Perfect if you're prepping for #Cisco, #AWS, #PMP, #AI, #Python, #Excel, or #Cybersecurity!
โœ… 100% Free
โœ… No signup traps
โœ… Instantly downloadable

๐Ÿ“˜ IT Certs E-book: https://bit.ly/4fJSoLP
โ˜๏ธ Cloud & AI Kits: https://bit.ly/3F3lc5B
๐Ÿ“Š Cybersecurity, Python & Excel: https://bit.ly/4mFrA4g
๐Ÿง  Skill Test (Free!): https://bit.ly/3PoKH39
Tag a friend & level up together ๐Ÿ’ช

๐ŸŒ Join the IT Study Group: https://chat.whatsapp.com/E3Vkxa19HPO9ZVkWslBO8s
๐Ÿ“ฒ 1-on-1 Exam Help: https://wa.link/k0vy3x
๐Ÿ‘‘Last 24 HOURS to grab Mid-Year Mega Sale prices๏ผDonโ€™t miss Lucky Draw๐Ÿ‘‡
https://bit.ly/43VgcbT
ds full archive.pdf.pdf
55.2 MB
Best Data Science Archive Notes

โœ‰๏ธ Our Telegram channels: https://www.tgoop.com/addlist/0f6vfFbEMdAwODBk

๐Ÿ“ฑ Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Please open Telegram to view this post
VIEW IN TELEGRAM
โค4๐Ÿ‘2
This media is not supported in your browser
VIEW IN TELEGRAM
๐‹๐จ๐ ๐ข๐ฌ๐ญ๐ข๐œ ๐‘๐ž๐ ๐ซ๐ž๐ฌ๐ฌ๐ข๐จ๐ง ๐„๐ฑ๐ฉ๐ฅ๐š๐ข๐ง๐ž๐ ๐ฌ๐ข๐ฆ๐ฉ๐ฅ๐ฒ

If youโ€™ve just started learning Machine Learning, ๐‹๐จ๐ ๐ข๐ฌ๐ญ๐ข๐œ ๐‘๐ž๐ ๐ซ๐ž๐ฌ๐ฌ๐ข๐จ๐ง is one of the most important and misunderstood algorithms.

Hereโ€™s everything you need to know ๐Ÿ‘‡

๐Ÿ โ‡จ ๐–๐ก๐š๐ญ ๐ข๐ฌ ๐‹๐จ๐ ๐ข๐ฌ๐ญ๐ข๐œ ๐‘๐ž๐ ๐ซ๐ž๐ฌ๐ฌ๐ข๐จ๐ง?

Itโ€™s a supervised ML algorithm used to predict probabilities and classify data into binary outcomes (like 0 or 1, Yes or No, Spam or Not Spam).

๐Ÿ โ‡จ ๐‡๐จ๐ฐ ๐ข๐ญ ๐ฐ๐จ๐ซ๐ค๐ฌ?

It starts like Linear Regression, but instead of outputting continuous values, it passes the result through a ๐ฌ๐ข๐ ๐ฆ๐จ๐ข๐ ๐Ÿ๐ฎ๐ง๐œ๐ญ๐ข๐จ๐ง to map the result between 0 and 1.

๐˜—๐˜ณ๐˜ฐ๐˜ฃ๐˜ข๐˜ฃ๐˜ช๐˜ญ๐˜ช๐˜ต๐˜บ = ๐Ÿ / (๐Ÿ + ๐žโป(๐ฐ๐ฑ + ๐›))

Here,
๐ฐ = weights
๐ฑ = inputs
๐› = bias
๐ž = Eulerโ€™s number (approx. 2.718)

๐Ÿ‘ โ‡จ ๐–๐ก๐ฒ ๐ง๐จ๐ญ ๐‹๐ข๐ง๐ž๐š๐ซ ๐‘๐ž๐ ๐ซ๐ž๐ฌ๐ฌ๐ข๐จ๐ง?

Because Linear Regression predicts any number from -โˆž to +โˆž, which doesnโ€™t make sense for probability.
We need outputs between 0 and 1 and thatโ€™s where the sigmoid function helps.

๐Ÿ’ โ‡จ ๐‹๐จ๐ฌ๐ฌ ๐…๐ฎ๐ง๐œ๐ญ๐ข๐จ๐ง ๐ฎ๐ฌ๐ž๐?

๐๐ข๐ง๐š๐ซ๐ฒ ๐‚๐ซ๐จ๐ฌ๐ฌ-๐„๐ง๐ญ๐ซ๐จ๐ฉ๐ฒ

โ„’ = โˆ’(y log(p) + (1 โˆ’ y) log(1 โˆ’ p))
Where y is the actual value (0 or 1), and p is the predicted probability

๐Ÿ“ โ‡จ ๐€๐ฉ๐ฉ๐ฅ๐ข๐œ๐š๐ญ๐ข๐จ๐ง๐ฌ ๐ข๐ง ๐ซ๐ž๐š๐ฅ ๐ฅ๐ข๐Ÿ๐ž:

๐„๐ฆ๐š๐ข๐ฅ ๐’๐ฉ๐š๐ฆ ๐ƒ๐ž๐ญ๐ž๐œ๐ญ๐ข๐จ๐ง
๐ƒ๐ข๐ฌ๐ž๐š๐ฌ๐ž ๐๐ซ๐ž๐๐ข๐œ๐ญ๐ข๐จ๐ง
๐‚๐ฎ๐ฌ๐ญ๐จ๐ฆ๐ž๐ซ ๐‚๐ก๐ฎ๐ซ๐ง ๐๐ซ๐ž๐๐ข๐œ๐ญ๐ข๐จ๐ง
๐‚๐ฅ๐ข๐œ๐ค-๐“๐ก๐ซ๐จ๐ฎ๐ ๐ก ๐‘๐š๐ญ๐ž ๐๐ซ๐ž๐๐ข๐œ๐ญ๐ข๐จ๐ง
๐๐ข๐ง๐š๐ซ๐ฒ ๐ฌ๐ž๐ง๐ญ๐ข๐ฆ๐ž๐ง๐ญ ๐œ๐ฅ๐š๐ฌ๐ฌ๐ข๐Ÿ๐ข๐œ๐š๐ญ๐ข๐จ๐ง

๐Ÿ” โ‡จ ๐•๐ฌ. ๐Ž๐ญ๐ก๐ž๐ซ ๐‚๐ฅ๐š๐ฌ๐ฌ๐ข๐Ÿ๐ข๐ž๐ซ๐ฌ

Itโ€™s fast, interpretable, and easy to implement, but it struggles with non-linearly separable data unlike Decision Trees or SVMs.

๐Ÿ• โ‡จ ๐‚๐š๐ง ๐ข๐ญ ๐ก๐š๐ง๐๐ฅ๐ž ๐ฆ๐ฎ๐ฅ๐ญ๐ข๐ฉ๐ฅ๐ž ๐œ๐ฅ๐š๐ฌ๐ฌ๐ž๐ฌ?

Yes, using One-vs-Rest (OvR) or Softmax in Multinomial Logistic Regression.

๐Ÿ– โ‡จ ๐„๐ฑ๐š๐ฆ๐ฉ๐ฅ๐ž ๐ข๐ง ๐๐ฒ๐ญ๐ก๐จ๐ง

from sklearn.linear_model import LogisticRegression
model = LogisticRegression()
model.fit(X_train, y_train)
pred = model.predict(X_test)


#LogisticRegression #MachineLearning #MLAlgorithms #SupervisedLearning #BinaryClassification #SigmoidFunction #PythonML #ScikitLearn #MLForBeginners #DataScienceBasics #MLExplained #ClassificationModels #AIApplications #PredictiveModeling #MLRoadmap

โœ‰๏ธ Our Telegram channels: https://www.tgoop.com/addlist/0f6vfFbEMdAwODBk

๐Ÿ“ฑ Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Please open Telegram to view this post
VIEW IN TELEGRAM
โค8๐Ÿ”ฅ2
Please open Telegram to view this post
VIEW IN TELEGRAM
๐Ÿ‘4โค1
ds full archive.pdf.pdf
55.2 MB
Best Data Science Archive Notes

โœ‰๏ธ Our Telegram channels: https://www.tgoop.com/addlist/0f6vfFbEMdAwODBk

๐Ÿ“ฑ Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Please open Telegram to view this post
VIEW IN TELEGRAM
โค2๐Ÿ‘1
๐Ÿ๐Ÿ“ฐ Linear Algebra in Python: Matrix Inverses and Least Squares โ€” https://realpython.com/python-linear-algebra/

#PythonProgramming #python

โœ‰๏ธ Our Telegram channels: https://www.tgoop.com/addlist/0f6vfFbEMdAwODBk

๐Ÿ“ฑ Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Please open Telegram to view this post
VIEW IN TELEGRAM
๐Ÿ‘2
This channels is for Programmers, Coders, Software Engineers.

0๏ธโƒฃ Python
1๏ธโƒฃ Data Science
2๏ธโƒฃ Machine Learning
3๏ธโƒฃ Data Visualization
4๏ธโƒฃ Artificial Intelligence
5๏ธโƒฃ Data Analysis
6๏ธโƒฃ Statistics
7๏ธโƒฃ Deep Learning
8๏ธโƒฃ programming Languages

โœ… https://www.tgoop.com/addlist/8_rRW2scgfRhOTc0

โœ… https://www.tgoop.com/Codeprogrammer
Please open Telegram to view this post
VIEW IN TELEGRAM
โค3๐Ÿ‘2
Top 50 LLM Interview Questions!

A comprehensive resource that covers traditional ML basics, model architectures, real-world case studies, and theoretical foundations.

๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡

โœ‰๏ธ Our Telegram channels: https://www.tgoop.com/addlist/0f6vfFbEMdAwODBk

๐Ÿ“ฑ Our WhatsApp channel: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Please open Telegram to view this post
VIEW IN TELEGRAM
โค1๐Ÿ‘1
2025/07/13 14:21:08
Back to Top
HTML Embed Code: