Desktop Notification with Python


#code #Python
🆔 @Python4all_pro

🎵 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


#code #Python
🆔 @Python4all_pro

Calendar month using Python



#code #Python
🆔 @Python4all_pro

21 پروژه پایتون از سطح مبتدی تا پیشرفته

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



#پروژه #Python
🆔 @Python4all_pro

⌨️ Useful Python Modules



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




#پروژه #Python
🆔 @Python4all_pro

IP Address Information using Python


#code #Python
🆔 @Python4all_pro

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


https://theunwindai.com/p/build-an-ai-rag-agent-with-web-access-using-gpt-4o



#code #Python
🆔 @Python4all_pro

Python Pandas Cheat Sheet


#cheat_sheet #Python
🆔 @Python4all_pro

🖥 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/#/


#Python
🆔 @Python4all_pro

🖥 py2many: Python to many CLike languages ​​transpiler

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

It supports many languages ​​such as Rust, C++, Julia, Kotlin, and others, and is also capable of generating Python code with type annotations.

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


#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
🆔 @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*

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

Python Tip

#python
#Python_tricks

🆔 @Python4all_pro

Create a Progress Bars using Python



#code #Python
🆔 @Python4all_pro

Google Earth Location using Python



#code #Python
🆔 @Python4all_pro

Build 50+ Python Applications for Beginners | 10 Lines of Code

https://morioh.com/p/351b8ec6db7f




#code #Python
🆔 @Python4all_pro

Top 3 High order functions in Python

#code #Python
🆔 @Python4all_pro

Convert an Image to a PDF file using Python


#code #Python
🆔 @Python4all_pro

دستیار هوش مصنوعی برای برنامه‌نویسان پایتون!

از وب سایت zzzcode.ai می تونید به عنوان یک دستیار تخصصی برای زبان پایتون، حوزه داده و هوش مصنوعی استفاده کنید. هم براتون کد مینویسه و هم کدهایی که بهش میدید رو توضیح میده. به عنوان نمونه من ازش خواستم که سورس کد مدل یادگیری ماشین GCNN روی توی پایتون بهم بده و خروجی تصویر رو داده. نمونه پرامپت داده شده:
Prompt:

Hi dear, I want to train a GCNN model on "MyDataset" dataset. Can you please write code in Python?


🔗https://zzzcode.ai/



#code #Python #هوش_مصنوعی
🆔 @Python4all_pro