π₯ Face swap on python.
π @CodeProgrammer
pip install --user opencv-python insightface matplotlib
# ΡΠΊΠ°ΡΠ°ΠΉ 'inswapper_128.onnx' ΠΎΡΡΡΠ΄Π° 'clck.ru/36ct6v' ΠΈ Π·Π°ΠΊΠΈΠ½Ρ Π² ΠΏΠ°ΠΏΠΊΡ Ρ ΠΊΠΎΠ΄ΠΎΠΌ
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('Π’Π£Π’ Π’ΠΠΠ ΠΠΠΠΠ ΠΠΠΠΠΠ')
π₯ Video: https://www.youtube.com/shorts/78CFNgTTX54π @CodeProgrammer
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Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.
This course includes:
42 hours on-demand video
5 coding exercises
39 articles
9 downloadable resources
π’ Price :- $20
Source :- https://www.udemy.com/course/machinelearning/
Contact @hussein_sheikho
Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.
This course includes:
42 hours on-demand video
5 coding exercises
39 articles
9 downloadable resources
π’ Price :- $20
Source :- https://www.udemy.com/course/machinelearning/
Contact @hussein_sheikho
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π
Create an Audiobook in Python
π https://www.tgoop.com/CodeProgrammer
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π https://www.tgoop.com/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()
π https://www.tgoop.com/CodeProgrammer
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Get and download all Udemy courses and other courses for only $10
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patreon.com/DataScienceBooks
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Daily importance services
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π₯ 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
π https://www.tgoop.com/CodeProgrammer
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A realtime sketch to image demo using LCM and the gradio library.
Source: https://github.com/flowtyone/flowty-realtime-lcm-canvas
π https://www.tgoop.com/CodeProgrammer
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Channel for who have a passion for -
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Channel for who have a passion for -
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Support Vector Machines in OpenCV
Article: https://machinelearningmastery.com/support-vector-machines-in-opencv/
π https://www.tgoop.com/CodeProgrammer
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Article: https://machinelearningmastery.com/support-vector-machines-in-opencv/
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π₯ Building and Evaluating Advanced RAG Applications
A new free course from deeplearning.ai on complex RAG (Retrieval Augmented Generation ) techniques has been released.π¦Ύ
This course teaches advanced LLM techniques that will help you generate good and relevant answers and...
deeplearning.ai/short-courses/building-evaluating-advanced-rag/
π https://www.tgoop.com/CodeProgrammer
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A new free course from deeplearning.ai on complex RAG (Retrieval Augmented Generation ) techniques has been released.π¦Ύ
This course teaches advanced LLM techniques that will help you generate good and relevant answers and...
deeplearning.ai/short-courses/building-evaluating-advanced-rag/
π https://www.tgoop.com/CodeProgrammer
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π 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://www.tgoop.com/CodeProgrammer
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https://github.com/pytube/pytube
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π₯ Calculate derivatives in Python
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β‘οΈ 8 free courses to master large language models:
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
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
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/
This course shows how to create LLM-based applications using API, Langchain ΠΈ W&B Prompts . He talks about developing, experimenting, and evaluating LLM-oriented applications.
https://www.wandb.courses/courses/building-llm-powered-apps
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
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
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
Covers topics such as Prompt Engineering, LLMOps, UX for language user interfaces, augmented language models, rapid LLM application development, future trends in LLM, fundamental concepts and walkthrough of askFSDL.
https://fullstackdeeplearning.com/llm-bootcamp/
https://www.tgoop.com/CodeProgrammer
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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
3- DeepLearningAI
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/
4- Weights_biases course
This course shows how to create LLM-based applications using API, Langchain ΠΈ W&B Prompts . He talks about developing, experimenting, and evaluating LLM-oriented applications.
https://www.wandb.courses/courses/building-llm-powered-apps
5- Introduction to LLMs course by google cloud
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
6- Databricks courses
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
7- Course "LangChain & Vector Databases in Production" from activeloopai, towards_AI and Intel
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
8- LLM Bootcamp
Covers topics such as Prompt Engineering, LLMOps, UX for language user interfaces, augmented language models, rapid LLM application development, future trends in LLM, fundamental concepts and walkthrough of askFSDL.
https://fullstackdeeplearning.com/llm-bootcamp/
https://www.tgoop.com/CodeProgrammer
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Cohere
Welcome to LLM University! | Cohere
LLM University (LLMU) offers in-depth, practical NLP and LLM training. Ideal for all skill levels. Learn, build, and deploy Language AI with Cohere.
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π₯ 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
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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π₯ Turn (almost) any Python command line program into a full GUI application with one line.
π GitHub: https://github.com/chriskiehl/Gooey
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π GitHub: https://github.com/chriskiehl/Gooey
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