Python Projects & Resources
57.1K subscribers
777 photos
342 files
329 links
Perfect channel to learn Python Programming ๐Ÿ‡ฎ๐Ÿ‡ณ
Download Free Books & Courses to master Python Programming
- โœ… Free Courses
- โœ… Projects
- โœ… Pdfs
- โœ… Bootcamps
- โœ… Notes

Admin: @Coderfun
Download Telegram
Built-in Data Types in Python ๐Ÿ‘†
โค9
Guys, Big Announcement!

Weโ€™ve officially hit 2 MILLION followers โ€” and itโ€™s time to take our Python journey to the next level!

Iโ€™m super excited to launch the 30-Day Python Coding Challenge โ€” perfect for absolute beginners, interview prep, or anyone wanting to build real projects from scratch.

This challenge is your daily dose of Python โ€” bite-sized lessons with hands-on projects so you actually code every day and level up fast.

Hereโ€™s what youโ€™ll learn over the next 30 days:

Week 1: Python Fundamentals

- Variables & Data Types (Build your own bio/profile script)

- Operators (Mini calculator to sharpen math skills)

- Strings & String Methods (Word counter & palindrome checker)

- Lists & Tuples (Manage a grocery list like a pro)

- Dictionaries & Sets (Create your own contact book)

- Conditionals (Make a guess-the-number game)

- Loops (Multiplication tables & pattern printing)

Week 2: Functions & Logic โ€” Make Your Code Smarter

- Functions (Prime number checker)

- Function Arguments (Tip calculator with custom tips)

- Recursion Basics (Factorials & Fibonacci series)

- Lambda, map & filter (Process lists efficiently)

- List Comprehensions (Filter odd/even numbers easily)

- Error Handling (Build a safe input reader)

- Review + Mini Project (Command-line to-do list)


Week 3: Files, Modules & OOP

- Reading & Writing Files (Save and load notes)

- Custom Modules (Create your own utility math module)

- Classes & Objects (Student grade tracker)

- Inheritance & OOP (RPG character system)

- Dunder Methods (Build a custom string class)

- OOP Mini Project (Simple bank account system)

- Review & Practice (Quiz app using OOP concepts)


Week 4: Real-World Python & APIs โ€” Build Cool Apps

- JSON & APIs (Fetch weather data)

- Web Scraping (Extract titles from HTML)

- Regular Expressions (Find emails & phone numbers)

- Tkinter GUI (Create a simple counter app)

- CLI Tools (Command-line calculator with argparse)

- Automation (File organizer script)

- Final Project (Choose, build, and polish your app!)

React with โค๏ธ if you're ready for this new journey

You can join our WhatsApp channel to access it for free: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1661
โค11๐Ÿ˜1
Machine Learning isn't easy!

Itโ€™s the field that powers intelligent systems and predictive models.

To truly master Machine Learning, focus on these key areas:

0. Understanding the Basics of Algorithms: Learn about linear regression, decision trees, and k-nearest neighbors to build a solid foundation.


1. Mastering Data Preprocessing: Clean, normalize, and handle missing data to prepare your datasets for training.


2. Learning Supervised Learning Techniques: Dive deep into classification and regression models, such as SVMs, random forests, and logistic regression.


3. Exploring Unsupervised Learning: Understand clustering techniques (K-means, hierarchical) and dimensionality reduction (PCA, t-SNE).


4. Mastering Model Evaluation: Use techniques like cross-validation, confusion matrices, ROC curves, and F1 scores to assess model performance.


5. Understanding Overfitting and Underfitting: Learn how to balance bias and variance to build robust models.


6. Optimizing Hyperparameters: Use grid search, random search, and Bayesian optimization to fine-tune your models for better performance.


7. Diving into Neural Networks and Deep Learning: Explore deep learning with frameworks like TensorFlow and PyTorch to create advanced models like CNNs and RNNs.


8. Working with Natural Language Processing (NLP): Master text data, sentiment analysis, and techniques like word embeddings and transformers.


9. Staying Updated with New Techniques: Machine learning evolves rapidlyโ€”keep up with emerging models, techniques, and research.



Machine learning is about learning from data and improving models over time.

๐Ÿ’ก Embrace the challenges of building algorithms, experimenting with data, and solving complex problems.

โณ With time, practice, and persistence, youโ€™ll develop the expertise to create systems that learn, predict, and adapt.

Data Science & Machine Learning Resources: https://topmate.io/coding/914624

Credits: https://t.iss.one/datasciencefun

Like if you need similar content ๐Ÿ˜„๐Ÿ‘

Hope this helps you ๐Ÿ˜Š

#datascience
โค2
Python Projects For Hacking
โค6
๐Ÿ‘4
Python Libraries for Data Science
โค5