en
Feedback
Coding Free Books | Python | AI

Coding Free Books | Python | AI

Open in Telegram

Best Channel for Programmers and Hackers All in one channel to learn ๐Ÿ‘‡ 1. Python 2. Ethical Hacking 3. Java 4. App development 5. Machine learning 6. Data structures 7. Algorithms Promotions: @coderfun

Show more

๐Ÿ“ˆ Analytical overview of Telegram channel Coding Free Books | Python | AI

Channel Coding Free Books | Python | AI (@codingwithsagar) in the English language segment is an active participant. Currently, the community unites 30 887 subscribers, ranking 6 252 in the Education category and 13 566 in the India region.

๐Ÿ“Š Audience metrics and dynamics

Since its creation on ะฝะตะฒั–ะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 30 887 subscribers.

According to the latest data from 21 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 148 over the last 30 days and by 0 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 3.76%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 161 views. Within the first day, a publication typically gains 0 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 4.
  • Thematic interests: Content is focused on key topics such as learning, link:-, css, algorithm, sql.

๐Ÿ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
โ€œBest Channel for Programmers and Hackers All in one channel to learn ๐Ÿ‘‡ 1. Python 2. Ethical Hacking 3. Java 4. App development 5. Machine learning 6. Data structures 7. Algorithms Promotions: @coderfunโ€

Thanks to the high frequency of updates (latest data received on 22 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

30 887
Subscribers
No data24 hours
-127 days
+14830 days
Posts Archive
โšก๏ธThe best job today is to be a trader This year, they earned an average of $20,000 a month, working from home, traveling or in a country house. And the smartest ones are making hundreds of thousands. Do you want the same? You don't need to be a genius to make money from deals, just start reading Evelyn's channel. She explains in detail how to make $4,000 in the first week just by copying her trades, without any risks or long training. โœ…Subscribe โ€” everything you need to get started is there: @trading_evelyn

Job Interview Questions & Free Resources ๐Ÿ‘‡๐Ÿ‘‡ https://bit.ly/4clYemH Like for more free resources โค๏ธ ENJOY LEARNING ๐Ÿ‘๐Ÿ‘

+6
Linux_ The_Ultimate_Guide.pdf4.72 MB

๐Ÿฑ ๐—™๐—ฅ๐—˜๐—˜ ๐—ฉ๐—ถ๐—ฟ๐˜๐˜‚๐—ฎ๐—น ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐—ป๐˜€๐—ต๐—ถ๐—ฝ๐˜€ ๐˜๐—ผ ๐—•๐—ผ๐—ผ๐˜€๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฅ๐—ฒ๐˜€๐˜‚๐—บ๐—ฒ๐Ÿ˜ These 100% free & remote virtual in
๐Ÿฑ ๐—™๐—ฅ๐—˜๐—˜ ๐—ฉ๐—ถ๐—ฟ๐˜๐˜‚๐—ฎ๐—น ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐—ป๐˜€๐—ต๐—ถ๐—ฝ๐˜€ ๐˜๐—ผ ๐—•๐—ผ๐—ผ๐˜€๐˜ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—ฅ๐—ฒ๐˜€๐˜‚๐—บ๐—ฒ๐Ÿ˜ These 100% free & remote virtual internships will help you develop in-demand skills from top global companies! No prior experience neededโ€”just sign up & start learning! ๐‹๐ข๐ง๐ค ๐Ÿ‘‡:- https://pdlink.in/4bajU4J Enroll For FREE & Get Certified ๐ŸŽ“

Dynamic Programming Was Really Hard for me, Until I found This. 1. DP for Beginners [Problems | Patterns | Sample Solutions] - https://lnkd.in/d5b9uJn6 2. DP Patterns - https://lnkd.in/dJPz8Dvn 3. Knapsack problems - https://lnkd.in/dE_rg6dd 4. How to solve DP-String? Template and 4 Steps to be followed - https://lnkd.in/dqhu3MZf 5. Dynamic Programming Questions thread - https://lnkd.in/d-pVR4rg 6. How to approach DP problems - https://lnkd.in/dwbh-XqJ 7. Iterative DP for subset sum problems - https://lnkd.in/djy5iDKE 8. DP problems summary (problem categorization) - https://lnkd.in/dbUrGV3C 9. Categorization of Leetcode DP problems - https://lnkd.in/dMqRZYrZ 10. Must do Dynamic Programming Category wise - https://lnkd.in/dFpneDKY 11. Dynamic programming is simple - https://lnkd.in/dk4emjPt 12. Dynamic Programming on subsets with examples - https://lnkd.in/dQBhzxBV

๐—–๐—ถ๐˜€๐—ฐ๐—ผ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ˜ Upgrade Your Tech Skills in 2025โ€”For FREE! ๐Ÿ”น Introduction t
๐—–๐—ถ๐˜€๐—ฐ๐—ผ ๐—™๐—ฅ๐—˜๐—˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ˜ Upgrade Your Tech Skills in 2025โ€”For FREE! ๐Ÿ”น Introduction to Cybersecurity ๐Ÿ”น Networking Essentials ๐Ÿ”น Introduction to Modern AI ๐Ÿ”น Discovering Entrepreneurship ๐Ÿ”น Python for Beginners ๐‹๐ข๐ง๐ค ๐Ÿ‘‡:- https://pdlink.in/4chn8Us Enroll For FREE & Get Certified ๐ŸŽ“

+3
๐Ÿ”ฐ Kotlin Resources Part 1๏ธโƒฃ

๐Ÿฐ ๐—™๐—ฅ๐—˜๐—˜ ๐—ฆ๐—ค๐—Ÿ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ˜ - Introduction to SQL (Simplilearn) - Intro to SQL (Kaggle) -
๐Ÿฐ ๐—™๐—ฅ๐—˜๐—˜ ๐—ฆ๐—ค๐—Ÿ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ˜ - Introduction to SQL (Simplilearn)  - Intro to SQL (Kaggle)  - Introduction to Database & SQL Querying  - SQL for Beginners โ€“ Microsoft SQL Server  Start Learning Today โ€“ 4 Free SQL Courses ๐‹๐ข๐ง๐ค ๐Ÿ‘‡:- https://pdlink.in/42nUsWr Enroll For FREE & Get Certified ๐ŸŽ“

+4
๐Ÿ“–Data Structure Using Python ๐Ÿ”ฐ React โค๏ธโ€๐Ÿ”ฅ for more

regarding the form survey on Google maps, there is a reward of 120 INR rich spend 2 minutes filling out the complete form. https://gleam.io/vZqfA/0328ptj

โŒจ๏ธ Take Screenshots using Python
โŒจ๏ธ Take Screenshots using Python

Python Cheatsheet-4.pdf1.53 MB

๐—•๐—ฟ๐—ฒ๐—ฎ๐—ธ ๐—œ๐—ป๐˜๐—ผ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜ โ€“ ๐—ก๐—ผ ๐—˜๐˜…๐—ฐ๐˜‚๐˜€๐—ฒ๐˜€!๐Ÿ˜ Want to learn Data Analytics, Python
๐—•๐—ฟ๐—ฒ๐—ฎ๐—ธ ๐—œ๐—ป๐˜๐—ผ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜ โ€“ ๐—ก๐—ผ ๐—˜๐˜…๐—ฐ๐˜‚๐˜€๐—ฒ๐˜€!๐Ÿ˜ Want to learn Data Analytics, Python, Power BI, and Machine Learning without spending a single rupee? Hereโ€™s your golden ticket! ๐ŸŽŸ๏ธ ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/3DMG9S5 ๐Ÿ”— Bookmark & Share This With Someone Who Needs It!

+4
Soranson_Python-Machine-Learning_RuLit_Me_683600.pdf8.14 KB

๐ŸŽ“ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ณ๐—ฟ๐—ผ๐—บ ๐—ข๐—ฝ๐—ฒ๐—ป ๐—จ๐—ป๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐˜€๐—ถ๐˜๐˜† โ€“ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป, ๐—š๐—ฟ๐—ผ๐˜„ & ๐—จ๐—ฝ๐˜€๐—ธ๐—ถ๐—น๐—น!๐Ÿ˜ If youโ€™re just s
๐ŸŽ“ ๐—™๐—ฟ๐—ฒ๐—ฒ ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ณ๐—ฟ๐—ผ๐—บ ๐—ข๐—ฝ๐—ฒ๐—ป ๐—จ๐—ป๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐˜€๐—ถ๐˜๐˜† โ€“ ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป, ๐—š๐—ฟ๐—ผ๐˜„ & ๐—จ๐—ฝ๐˜€๐—ธ๐—ถ๐—น๐—น!๐Ÿ˜ If youโ€™re just starting your learning journey or looking to level up your skillsโ€”this is your golden opportunity! ๐ŸŒŸ ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/4cuo73X โณ Donโ€™t miss outโ€”bookmark this for later!

Important questions to ace your machine learning interview with an approach to answer: 1. Machine Learning Project Lifecycle:    - Define the problem    - Gather and preprocess data    - Choose a model and train it    - Evaluate model performance    - Tune and optimize the model    - Deploy and maintain the model 2. Supervised vs Unsupervised Learning:    - Supervised Learning: Uses labeled data for training (e.g., predicting house prices from features).    - Unsupervised Learning: Uses unlabeled data to find patterns or groupings (e.g., clustering customer segments). 3. Evaluation Metrics for Regression:    - Mean Absolute Error (MAE)    - Mean Squared Error (MSE)    - Root Mean Squared Error (RMSE)    - R-squared (coefficient of determination) 4. Overfitting and Prevention:    - Overfitting: Model learns the noise instead of the underlying pattern.    - Prevention: Use simpler models, cross-validation, regularization. 5. Bias-Variance Tradeoff:    - Balancing error due to bias (underfitting) and variance (overfitting) to find an optimal model complexity. 6. Cross-Validation:    - Technique to assess model performance by splitting data into multiple subsets for training and validation. 7. Feature Selection Techniques:    - Filter methods (e.g., correlation analysis)    - Wrapper methods (e.g., recursive feature elimination)    - Embedded methods (e.g., Lasso regularization) 8. Assumptions of Linear Regression:    - Linearity    - Independence of errors    - Homoscedasticity (constant variance)    - No multicollinearity 9. Regularization in Linear Models:    - Adds a penalty term to the loss function to prevent overfitting by shrinking coefficients. 10. Classification vs Regression:     - Classification: Predicts a categorical outcome (e.g., class labels).     - Regression: Predicts a continuous numerical outcome (e.g., house price). 11. Dimensionality Reduction Algorithms:     - Principal Component Analysis (PCA)     - t-Distributed Stochastic Neighbor Embedding (t-SNE) 12. Decision Tree:     - Tree-like model where internal nodes represent features, branches represent decisions, and leaf nodes represent outcomes. 13. Ensemble Methods:     - Combine predictions from multiple models to improve accuracy (e.g., Random Forest, Gradient Boosting). 14. Handling Missing or Corrupted Data:     - Imputation (e.g., mean substitution)     - Removing rows or columns with missing data     - Using algorithms robust to missing values 15. Kernels in Support Vector Machines (SVM):     - Linear kernel     - Polynomial kernel     - Radial Basis Function (RBF) kernel Data Science Interview Resources ๐Ÿ‘‡๐Ÿ‘‡ https://topmate.io/coding/914624 Like for more ๐Ÿ˜„

๐Ÿฑ ๐—™๐—ฅ๐—˜๐—˜ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ˜ Whether youโ€™re a complete beginner or lo
๐Ÿฑ ๐—™๐—ฅ๐—˜๐—˜ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ˜ Whether youโ€™re a complete beginner or looking to level up, these courses cover Excel, Power BI, Data Science, and Real-World Analytics Projects to make you job-ready. ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/3DPkrga All The Best ๐ŸŽŠ

How Promotion in TCS takes place ๐Ÿ‘‡๐Ÿ‘‡ https://datasimplifier.com/promotion-in-tcs/

๐Ÿ”ฐ Complete Python Handwritten Notes! Sharing this file again cause some people are getting problems to download this book! React โ€œโค๏ธโ€ if you want more ebooks & notes

๐—ง๐—ผ๐—ฝ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€ ๐—ข๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด ๐—™๐—ฅ๐—˜๐—˜ ๐˜ƒ๐—ถ๐—ฟ๐˜๐˜‚๐—ฎ๐—น ๐—ฒ๐˜…๐—ฝ๐—ฒ๐—ฟ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ฝ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ๐˜€๐Ÿ˜ Want to work on re
๐—ง๐—ผ๐—ฝ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€ ๐—ข๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด ๐—™๐—ฅ๐—˜๐—˜ ๐˜ƒ๐—ถ๐—ฟ๐˜๐˜‚๐—ฎ๐—น ๐—ฒ๐˜…๐—ฝ๐—ฒ๐—ฟ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐—ฝ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ๐˜€๐Ÿ˜ Want to work on real industry tasks, develop in-demand skills, and boost your resumeโ€”all for FREE?   Your dream career starts with real experienceโ€”grab this opportunity today! ๐‹๐ข๐ง๐ค๐Ÿ‘‡:- https://pdlink.in/4bCyUIM ๐Ÿ’ก No experience requiredโ€”just learn, upskill & build your portfolio! ๐Ÿš€