Python | Machine Learning | Coding | R
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List of our channels:
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Discover powerful insights with Python, Machine Learning, Coding, and Rβ€”your essential toolkit for data-driven solutions, smart alg

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πŸ”₯ flowty-realtime-lcm-canvas

A realtime sketch to image demo using LCM and the gradio library.

Source: https://github.com/flowtyone/flowty-realtime-lcm-canvas

πŸ‘Œ https://t.me/CodeProgrammer

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Artificial Intelligence && Deep Learning
Channel for who have a passion for -

* Artificial Intelligence
* Machine Learning
* Deep Learning
* Data Science
* Computer vision
* Image Processing
* Research Papers

https://t.me/DeepLearning_ai

https://t.me/MachineLearning_Programming
Support Vector Machines in OpenCV

Article: https://machinelearningmastery.com/support-vector-machines-in-opencv/

πŸ‘Œ https://t.me/CodeProgrammer

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πŸ”₯ Building and Evaluating Advanced RAG Applications

A new free course from deeplearning.ai on complex RAG (Retrieval Augmented Generation ) techniques has been released.🦾

This course teaches advanced LLM techniques that will help you generate good and relevant answers and...

deeplearning.ai/short-courses/building-evaluating-advanced-rag/

πŸ‘Œ https://t.me/CodeProgrammer

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🎞 Pytube is a lightweight #Python library that enables you to download #YouTube videos and playlists in specific formats and resolutions.

https://github.com/pytube/pytube

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Programmers joked with each other πŸ˜‚
STOP WORKING – START EARNINGπŸ†

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https://t.me/+mdMjDnomUa83NWJk
πŸ–₯ Calculate derivatives in Python

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πŸ–₯ Hitchhiker's Guide to Python

Python Best Practices Guidebook

A guide to best practices for installing, configuring and using Python on a daily basis, including pip, numpy, virtualenv and more.

Resources: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A/110
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πŸ–₯ Turn (almost) any Python command line program into a full GUI application with one line.

πŸ”— GitHub: https://github.com/chriskiehl/Gooey

https://t.me/CodeProgrammer

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πŸ” Lock Your Photos using Python

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⭕️ Data science learning roadmap in 2024
πŸ“‚ with all videos, projects, books and pamphlets

πŸ‘¨πŸ»β€πŸ’» Krish Naik, one of the famous Indian data scientists, with more than 845 thousand users on his YouTube channel , has published a comprehensive roadmap for learning data science in the new year.

πŸ”· This roadmap is excellent for all those who are planning to start learning data science or are experienced in this field and want to get acquainted with the latest training in this field.πŸ‘ŒπŸΌ

βœ… This comprehensive roadmap includes learning from scratch Python, machine learning, deep learning, MLOPS, LLM, Generative AI and many other things.


β”Œ 🏷 Data Science Perfect Roadmap
β”” πŸ“ Roadmap To Learn Data Science 2024

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πŸ–₯ DataQA extractor

App to extract structured fields into a spreadsheet from unstructured text.

DataQA extractor is a Python application for extracting structured fields from unstructured text and adding them to a spreadsheet.

GitHub: https://github.com/dataqa/extractor

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πŸ”… Compress Images

from PIL import Image
in_img = 'input.png'
out_img = 'compressed.png'

# Open the image
with Image.open(in_img) as img:
# Save the compressed image
img.save(out_img, 'PNG', quality=80)

print(f"Image compressed successfully!")

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Deep Learning with PyTorch Cheat Sheet
Learn everything you need to know about PyTorch in this convenient cheat sheet

PyTorch is an open-source machine learning library primarily developed by Facebook's AI Research Lab (FAIR). It is widely used for various machine learning and deep learning tasks, including neural network development, natural language processing (NLP), computer vision, and reinforcement learning. In this cheat sheet, learn all the fundamentals of working with PyTorch in one convenient location!

Download πŸ‘‡πŸ‘‡πŸ‘‡
@codeprogrammer Deep Learning with PyTorch Cheat Sheet.pdf
5.8 MB
Deep Learning with PyTorch Cheat Sheet

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πŸ‘€ The best free data science learning courses

πŸ‘¨πŸ»β€πŸ’» I want today I shared with you five of the best free data science learning courses that helped me become a successful data scientist and get a job at Google . πŸ‘‡πŸΌ

β”Œ 🏷 CS229: Machine Learning
β”” ◼️
LINK

β”Œ 🏷 MIT: Linear Algebra
β”” ◼️
LINK

β”Œ 🏷 MIT: Introduction to Algorithms
β”” ◼️
LINK

β”Œ 🏷 MIT: Applied Probability
β”” ◼️
LINK

β”Œ 🏷 Stanford: Relational Databases & SQL
β”” ◼️
LINK

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