پایتون | Data Science | Machine Learning

#NumPy cheat sheet for #datascience :

*Array Creation*

1. numpy.array() - Create an array from a list or other iterable.
2. numpy.zeros() - Create an array filled with zeros.
3. numpy.ones() - Create an array filled with ones.
4. numpy.empty() - Create an empty array.
5. numpy.arange() - Create an array with evenly spaced values.
6. numpy.linspace() - Create an array with evenly spaced values.

*Array Operations*

1. + - Element-wise addition.
2. - - Element-wise subtraction.
3. * - Element-wise multiplication.
4. / - Element-wise division.
5. ** - Element-wise exponentiation.
6. numpy.sum() - Sum of all elements.
7. numpy.mean() - Mean of all elements.
8. numpy.median() - Median of all elements.
9. numpy.std() - Standard deviation.
10. numpy.var() - Variance.

*Array Indexing*

1. arr[i] - Access ith element.
2. arr[i:j] - Access slice from ith to jth element.
3. arr[i:j:k] - Access slice with step k.

*Array Reshaping*

1. arr.reshape() - Reshape array.
2. arr.flatten() - Flatten array.
3. arr.ravel() - Flatten array.

*Array Manipulation*

1. numpy.concatenate() - Concatenate arrays.
2. numpy.split() - Split array.
3. numpy.transpose() - Transpose array.
4. numpy.flip() - Flip array.

*Mathematical Functions*

1. numpy.sin() - Sine.
2. numpy.cos() - Cosine.
3. numpy.tan() - Tangent.
4. numpy.exp() - Exponential.
5. numpy.log() - Natural logarithm.

*Statistical Functions*

1. numpy.min() - Minimum value.
2. numpy.max() - Maximum value.
3. numpy.percentile() - Percentile.
4. numpy.quantile() - Quantile.

*Random Number Generation*

1. numpy.random.rand() - Random numbers.
2. numpy.random.normal() - Normal distribution.
3. numpy.random.uniform() - Uniform distribution.

*Linear Algebra*

1. numpy.dot() - Dot product.
2. numpy.matmul() - Matrix multiplication.
3. numpy.linalg.inv() - Matrix inverse.

#cheat_sheet #Python
🆔 @Python4all_pro

#NumPy cheat sheet for #datascience :

*Array Creation*

1. numpy.array() - Create an array from a list or other iterable.
2. numpy.zeros() - Create an array filled with zeros.
3. numpy.ones() - Create an array filled with ones.
4. numpy.empty() - Create an empty array.
5. numpy.arange() - Create an array with evenly spaced values.
6. numpy.linspace() - Create an array with evenly spaced values.

*Array Operations*

1. + - Element-wise addition.
2. - - Element-wise subtraction.
3. * - Element-wise multiplication.
4. / - Element-wise division.
5. ** - Element-wise exponentiation.
6. numpy.sum() - Sum of all elements.
7. numpy.mean() - Mean of all elements.
8. numpy.median() - Median of all elements.
9. numpy.std() - Standard deviation.
10. numpy.var() - Variance.

*Array Indexing*

ادامه در پست بعد👇

#cheat_sheet #Python
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The py2many tool helps you translate Python code into code in various languages, including Rust.

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To translate the code, use a command in the terminal, after which the generated code is compiled.

Documentation with instructions for installing the necessary libraries and formatters is available on the project website.


🔗 GitHub


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🖥 Hallo2:Long-Duration and High-Resolution Audio-driven Portrait Image Animation

Python project for long duration, high resolution portrait animation.

▪ GitHub: https://github.com/fudan-generative-vision/hallo2
▪ Project: https://fudan-generative-vision.github.io/hallo2/#/


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Python Pandas Cheat Sheet


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Build an AI RAG agent with web access using GPT-4o in just 15 lines of Python Code (step-by-step instructions):


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IP Address Information using Python


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365 Days Python Challenge https://bit.ly/3Rr3OrM




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⌨️ Useful Python Modules



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21 پروژه پایتون از سطح مبتدی تا پیشرفته

https://morioh.com/p/bab182ed697a?f=5c21fb01c16e2556b555ab32



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Calendar month using Python



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🎵 UVR5 UI 🎵

The perfect Python tool to remove voice from audio using the user-friendly Gradio UI.

👉 This project is based on python-audio-separator (CLI version of UVR5).



▪Github
▪Colab


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Desktop Notification with Python


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تبدیل متن به مقادیر عددی در پایتون

Numerizer

$ pip install numerizer

>>> from numerizer import numerize
>>> numerize('forty two')
'42'
>>> numerize('forty-two')
'42'
>>> numerize('four hundred and sixty two')
'462'
>>> numerize('one fifty')
'150'
>>> numerize('twelve hundred')
'1200'
>>> numerize('twenty one thousand four hundred and seventy three')
'21473'
>>> numerize('one million two hundred and fifty thousand and seven')
'1250007'
>>> numerize('one billion and one')
'1000000001'
>>> numerize('nine and three quarters')
'9.75'
>>> numerize('platform nine and three quarters')
'platform 9.75'

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Build a Business Analytics Dashboard  Website using Python and MySQL



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Master Python programming in 15 days with Free Resources 👇

Days 1-3: Introduction to Python
- Day 1: Start by installing Python on your computer.
- Day 2: Learn the basic syntax and data types in Python (variables, numbers, strings).
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Days 4-6: Control Structures
- Day 4: Understand conditional statements (if, elif, else).
- Day 5: Learn about loops (for and while) and iterators.
- Day 6: Work on small projects to practice using conditionals and loops.

Days 7-9: Data Structures
- Day 7: Learn about lists and how to manipulate them.
- Day 8: Explore dictionaries and sets.
- Day 9: Understand tuples and lists comprehensions.

Days 10-12: Functions and Modules
- Day 10: Learn how to define functions in Python.
- Day 11: Understand scope and global vs. local variables.
- Day 12: Explore Python's module system and create your own modules.

Days 13-15: Intermediate Concepts
- Day 13: Work with file handling and I/O operations.
- Day 14: Learn about exceptions and error handling.
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Check Battery status using Python



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مجموعه چیت شیت های کاربردی

1. Python: https://t.co/piKNCap4OM
2. Pandas : https://t.co/khYH8blvbp
3. NumPy: https://t.co/bLQJ7QwpLJ
4. Matplotlib: https://t.co/FetNAcfbNs
5. Seaborn: https://t.co/M5ATDFl74d
6. Scikit-learn? https://t.co/3G7xEehIWC
7. TensorFlow: https://t.co/YEpQ9XO8le
8. Keras: https://t.co/3f4oKzUkkz
9. PyTorch: https://t.co/EwvqWF0gtN
10. SQL: https://t.co/qkePCfAgdD
11. R: https://t.co/BHhM7z6YE5
12. Git: https://t.co/tn4BdsdyJP
13. AWS https://t.co/ZQ1JckpXtM
14. Azure https://t.co/CM3ORVWR9s
15. Google Cloud Platform: https://t.co/q1eRcWJ5kH
16. Dockr : https://t.co/2ncSV6K2gl
17. Kubernetes https://t.co/mjo3mwcR5F
18. Linux Command Line: https://t.co/vKmygIJ68B
19. Jupyter Notebook https://t.co/9Bet0esetC
20. Data Wrangling:https://t.co/0sexNfthZG
21. Data Visualization: https://t.co/hKWpqsTvvt



#cheat_sheet #Python #library

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Text wrapping using Python Libraries



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