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Our new channel - Datasets repositories

https://t.me/datasets1

🖥 Awesome Python Awesome

A curated list of awesome Python frameworks, libraries, software and resources.

https://github.com/vinta/awesome-python

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🖥 Face swap on python.

pip install --user opencv-python insightface matplotlib
# скачай 'inswapper_128.onnx' отсюда 'clck.ru/36ct6v' и закинь в папку с кодом
import cv2
import insightface
from insightface.app import FaceAnalysis
import matplotlib.pyplot as plt

app = FaceAnalysis(name='buffalo_l')
app.prepare(ctx_id=0, det_size=(640, 640))
swapper = insightface.model_zoo.get_model('inswapper_128.onnx')

def swap_faces(img):
img = cv2.imread(img)
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
ax.imshow(img[:,:,::-1])
ax.axis('off'); plt.show()
faces = app.get(img)
face1, face2 = faces[0], faces[1]
imgnew = img.copy()
imgnew = swapper.get(imgnew, face1, face2, paste_back=True)
imgnew = swapper.get(imgnew, face2, face1, paste_back=True)
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
ax.imshow(imgnew[:,:,::-1])
ax.axis('off'); plt.show()
return imgnew


swap_faces('ТУТ ТВОЁ ИЗОБРАЖЕНИЕ')



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✅ By: https://t.me/Python53

🔅 Create an Audiobook in Python

👌 https://t.me/CodeProgrammer

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import PyPDF2
import pyttsx3
# Read the pdf by specifying the path in your computer 
pdfReader = PyPDF2.PdfFileReader(open('clcoding.pdf', 'rb'))
# Get the handle to speaker
speaker = pyttsx3.init()
# split the pages and read one by one
for page_num in range(pdfReader.numPages): 
    text = pdfReader.getPage(page_num).extractText() 
    speaker.say(text)
    speaker.runAndWait()
# stop the speaker after completion 
speaker.stop() 
# save the audiobook at specified path 
engine.save_to_file(text, 'E:\audio.mp3') 
engine.runAndWait()

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Get and download all Udemy courses and other courses for only $10

Create an account on Patreon
patreon.com/DataScienceBooks

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🔥 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

👌 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
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* Computer vision
* Image Processing
* Research Papers

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https://t.me/MachineLearning_Programming

Support Vector Machines in OpenCV

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

👌 https://t.me/CodeProgrammer

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🔥 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/

👌 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

https://t.me/CodeProgrammer

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🖥 Calculate derivatives in Python

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⚡️ 8 free courses to master large language models:

1- LLM University

The course provides an understanding of how LLM work, their practical applications, and guides students in using LLMs to build and deploy applications.
https://docs.cohere.com/docs/llmu

2- hugging face NLP course

This course provides comprehensive knowledge of Hugging Face transformers, datasets, tokenizers, and the Accelerate tool in the field of Natural Language Processing (NLP).
https://huggingface.co/learn/nlp-course/chapter1/1

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A collection of free courses created in collaboration with many companies such as LangChain, OpenAI, Google, Weights & Biases, Microsoft and others.
https://www.deeplearning.ai/short-courses/

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This course shows how to create LLM-based applications using API, Langchain и W&B Prompts . He talks about developing, experimenting, and evaluating LLM-oriented applications.
https://www.wandb.courses/courses/building-llm-powered-apps

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An introductory level course covering what LLMs are, their use cases, and how to improve LLM performance using prompt tuning
https://www.cloudskillsboost.google/course_templates/539

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The program includes two courses: " LLMs: Application through Production " and " LLMs: Foundation Models from the Ground Up "
https://www.databricks.com/blog/enroll-our-new-expert-led-large-language-models-llms-courses-edx

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The three-course series will provide students with the knowledge and skills to learn, fine-tune, and integrate LLM into production.
https://learn.activeloop.ai/courses/langchain

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https://fullstackdeeplearning.com/llm-bootcamp/

https://t.me/CodeProgrammer

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🖥 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