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πŸ–₯ Harvard's popular CS50 series has an intro to Python course taught by David J. Malan himself.

Harvard's popular CS50 course series includes an Introduction to Python course taught by David Jay Malan himself.

The course covers Python fundamentals such as loops and conditions, and writing and using APIs.

Along the way, you'll build an application using frameworks such as Django and React.

Course: https://cs50.harvard.edu/python/2022/

Videos: https://www.youtube.com/watch?v=nLRL_NcnK-4

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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CS25: Transformers United V3

New lectures on the course on Transformers from Stanford! Stanford CS 25 " Transformers United " featured celebrity guests such as Andriy Karpaty, Noam Brown, Lukas Beyer and Geoff Hinton himself!

A new report has been released on the creation and recipes for creating universal AI agents in open worlds:

🟒 MineDojo : an open framework and multimodal database for training Minecraft agents.

🟒 Voyager : agent for lifelong learning in Minecraft based on LLM.

🟒 Eureka: GPT-4 develops reward functions to teach a robot hand to turn a knob.

🟒 VIMA : one of the earliest multimodal LLMs.

🟒A look into the future: promising areas of research.

β˜‘οΈ Slides : https://drive.google.com/file/d/1lWIhijUaTZkkWOC_YwZHMoI0h7EAWVPL/view

πŸ“‘ Lectures : https://web.stanford.edu/class/cs25

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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πŸ“Œ Convert CSV to JSON

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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Which of the following is not a Python Data Type?
Anonymous Quiz
5%
int
11%
string
47%
char
38%
set
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πŸ”… Convert Video to Audio using Python

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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πŸ–₯ Crash Course on Python (From google)

Enroll Link: https://clcoding.com/2023/10/crash-course-on-python-from-google.html

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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Deep Learning and machine learning

πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡
@Machine_learn
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20231105-26861-1ou7ajp.gif
441.8 KB
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Introducing LazyPredict! πŸš€

A Python library that enables you to train, test, and evaluate multiple ML models at once using just a few lines of code.

Install:
pip install lazypredict

πŸ–₯ Github: https://github.com/shankarpandala/lazypredict

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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πŸ‘‰ Awesome Computer Vision

Awesome Books, Courses, Papers, Software, Datasets, Pre-trained Computer Vision Models, Tutorials, Talks, Blogs, Links and Songs related to Computer Vision.

πŸ”— GitHub: https://github.com/jbhuang0604/awesome-computer-vision

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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πŸ‘‰ Pytorch

This repository has a collection of best tutorials, projects, libraries, videos, papers, books and anything related to the incredible PyTorch.

πŸ”— GitHub: https://github.com/ritchieng/the-incredible-pytorch

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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πŸ–₯ Python code to find info about Chemical Formula

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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πŸ‘‰ AI Expert Roadmap

This ultimate repository for AI contains roadmaps for:

πŸ”Ή Artificial Intelligence
πŸ”Ή Machine Learning
πŸ”Ή Deep Learning
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πŸ”Ή Data Science

Link: https://github.com/AMAI-GmbH/AI-Expert-Roadmap

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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πŸ–₯ Awesome Python Awesome

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

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

πŸ‘Œ https://www.tgoop.com/CodeProgrammer

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365 data science courses

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πŸ–₯ Face swap on python.

pip install --user opencv-python insightface matplotlib
# скачай 'inswapper_128.onnx' ΠΎΡ‚ΡΡŽΠ΄Π° 'clck.ru/36ct6v' ΠΈ закинь Π² ΠΏΠ°ΠΏΠΊΡƒ с 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’Π’ΠžΠ Π˜Π—ΠžΠ‘Π ΠΠ–Π•ΠΠ˜Π•')


πŸŽ₯ Video: https://www.youtube.com/shorts/78CFNgTTX54

πŸ‘Œ @CodeProgrammer
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🌴Machine Learning A-Zβ„’: AI, Python & R + ChatGPT Bonus [2023] 🌴

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

🟒 Price :- $20

Source :- https://www.udemy.com/course/machinelearning/

Contact @hussein_sheikho
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❀️‍πŸ”₯Hacking the WIFI password❀️‍πŸ”₯

βœ… By: https://www.tgoop.com/Python53
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