๐ฒ Awesome useful Python scripts
Useful ready-made Python scripts.
1. JSON โ๏ธ CSV (Fig.1)
2. Password generator (Fig.2)
3. String search from several files (Fig.3)
4. Retrieving all links from a given web page (Fig.4)
5. Add a watermark (Fig.5)
6. Parser and image loader from WEB page (Fig.6)
7. Sorting the download folder (Fig.7)
8. Bulk email sending from a CSV file (Fig.8)
9. Obtaining the IP address and hostname of the website (Fig.9)
10. Progress bar of the terminal (Fig.10)
๐ Scripts: https://uproger.com/udivitelnye-sczenarii-python/
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Useful ready-made Python scripts.
1. JSON โ๏ธ CSV (Fig.1)
2. Password generator (Fig.2)
3. String search from several files (Fig.3)
4. Retrieving all links from a given web page (Fig.4)
5. Add a watermark (Fig.5)
6. Parser and image loader from WEB page (Fig.6)
7. Sorting the download folder (Fig.7)
8. Bulk email sending from a CSV file (Fig.8)
9. Obtaining the IP address and hostname of the website (Fig.9)
10. Progress bar of the terminal (Fig.10)
๐ Scripts: https://uproger.com/udivitelnye-sczenarii-python/
https://www.tgoop.com/CodeProgrammer
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๐ผ Briefcase
Briefcase is a tool for converting a Python project into a standalone native application.
โช Github: https://github.com/beeware/briefcase
โชTutorial: https://briefcase.readthedocs.io/en/stable/
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Briefcase is a tool for converting a Python project into a standalone native application.
โช Github: https://github.com/beeware/briefcase
โชTutorial: https://briefcase.readthedocs.io/en/stable/
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Python | Machine Learning | Coding | R
Photo
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How to Perform Face Detection with Deep Learning
Face detection is a computer vision problem that involves finding faces in photos.
It is a trivial problem for humans to solve and has been solved reasonably well by classical feature-based techniques, such as the cascade classifier. More recently deep learning methods have achieved state-of-the-art results on standard benchmark face detection datasets. One example is the Multi-task Cascade Convolutional Neural Network, or MTCNN for short.
In this tutorial, you will discover how to perform face detection in Python using classical and deep learning models.
https://machinelearningmastery.com/how-to-perform-face-detection-with-classical-and-deep-learning-methods-in-python-with-keras/
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Face detection is a computer vision problem that involves finding faces in photos.
It is a trivial problem for humans to solve and has been solved reasonably well by classical feature-based techniques, such as the cascade classifier. More recently deep learning methods have achieved state-of-the-art results on standard benchmark face detection datasets. One example is the Multi-task Cascade Convolutional Neural Network, or MTCNN for short.
In this tutorial, you will discover how to perform face detection in Python using classical and deep learning models.
https://machinelearningmastery.com/how-to-perform-face-detection-with-classical-and-deep-learning-methods-in-python-with-keras/
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Python | Machine Learning | Coding | R
Photo
๐ฅ Free Courses and Guides That Will Teach You How to Master AI:
๐ Elements of AI
https://elementsofai.com
๐ Learn Prompting
https://learnprompting.org
๐ Machine Learning
https://edx.org/learn/machine-learning/harvard-university-data-science-machine-learning
๐ AI for everyone
https://coursera.org/learn/ai-for-everyone
๐ 500+ AI Chatbot Prompt Templates
https://theveller.gumroad.com/l/ChatGPTPromptTemplates-byTheVeller
๐ Prompt Engineering
https://youtu.be/_ZvnD73m40o
๐ ChatGPT Prompt Engineering for Developers
https://deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers
๐ Google โ AI for Anyone
https://edx.org/learn/artificial-intelligence/google-google-ai-for-anyone
๐ Microsoft โ AI For Beginners
https://microsoft.github.io/AI-For-Beginners
๐ IBM โ AI for Everyone: Master the Basics
https://edx.org/learn/artificial-intelligence/ibm-ai-for-everyone-master-the-basics
๐ Google โ Introduction to Generative AI
https://cloudskillsboost.google/journeys/118
๐ DeepLearning โ Finetuning LLMs
https://deeplearning.ai/short-courses/finetuning-large-language-models
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๐ Elements of AI
https://elementsofai.com
๐ Learn Prompting
https://learnprompting.org
๐ Machine Learning
https://edx.org/learn/machine-learning/harvard-university-data-science-machine-learning
๐ AI for everyone
https://coursera.org/learn/ai-for-everyone
๐ 500+ AI Chatbot Prompt Templates
https://theveller.gumroad.com/l/ChatGPTPromptTemplates-byTheVeller
๐ Prompt Engineering
https://youtu.be/_ZvnD73m40o
๐ ChatGPT Prompt Engineering for Developers
https://deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers
๐ Google โ AI for Anyone
https://edx.org/learn/artificial-intelligence/google-google-ai-for-anyone
๐ Microsoft โ AI For Beginners
https://microsoft.github.io/AI-For-Beginners
๐ IBM โ AI for Everyone: Master the Basics
https://edx.org/learn/artificial-intelligence/ibm-ai-for-everyone-master-the-basics
๐ Google โ Introduction to Generative AI
https://cloudskillsboost.google/journeys/118
๐ DeepLearning โ Finetuning LLMs
https://deeplearning.ai/short-courses/finetuning-large-language-models
https://www.tgoop.com/CodeProgrammer
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๐ฅ Get domain name information using Python
$pip install whois
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$pip install whois
$pip install whois
>>> import whois
>>> domain = whois.query('google.com')
>>> print(domain.dict)
{
'expiration_date': datetime.datetime(2020, 9, 14, 0, 0),
'last_updated': datetime.datetime(2011, 7, 20, 0, 0),
'registrar': 'MARKMONITOR INC.',
'name': 'google.com',
'creation_date': datetime.datetime(1997, 9, 15, 0, 0)
}
>>> print(domain.name)
google.com
>>> print(domain.expiration_date)
2024-09-14 00:00:00
๐ Github: https://github.com/DannyCork/python-whoishttps://www.tgoop.com/CodeProgrammer
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๐ฅ Free Certification Courses from Google to try in 2023.
1. Basics of Machine Learning
https://grow.google/intl/en_in/
2. Machine Learning Crash Course
https://coursya.com/product/machine-learning-crash-course
3. Project Execution: Running the Project
https://coursera.org/learn/project-execution-google
4. Foundations of Project Management
https://coursera.org/learn/project-management-foundations
5. Project Initiation: Starting a Successful Project
https://coursera.org/learn/project-initiation-google
6. Project Planning: Putting It All Together
https://coursera.org/learn/project-planning-google
7. Google Analytics for Power Users
https://coursya.com/product/google-analytics-certification-coursya
8. Fundamentals of digital marketing
https://skillshop.exceedlms.com/student/collection/654330-digital-marketing?locale=en-GB
9. Python Basics for Data Analysis
https://coursya.com/product/learn-python-basics-for-data-analysis
10. Data Science Foundations
https://grow.google/intl/en_in/
11. Advanced Google Analytics
https://coursera.org/professional-certificates/google-data-analytics
12. Google Cloud Computing Foundations:
https://cloudskillsboost.google/course_templates/153
13. Data, ML, and AI in Google Cloud
https://coursya.com/product/google-cloud-computing-foundations-data-ml-and-ai-in-google-cloud-google-cloud-skills-boost
14. Agile Project Management
https://coursera.org/learn/agile-project-management
15. Google Project Management
https://coursera.org/professional-certificates/google-project-management
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1. Basics of Machine Learning
https://grow.google/intl/en_in/
2. Machine Learning Crash Course
https://coursya.com/product/machine-learning-crash-course
3. Project Execution: Running the Project
https://coursera.org/learn/project-execution-google
4. Foundations of Project Management
https://coursera.org/learn/project-management-foundations
5. Project Initiation: Starting a Successful Project
https://coursera.org/learn/project-initiation-google
6. Project Planning: Putting It All Together
https://coursera.org/learn/project-planning-google
7. Google Analytics for Power Users
https://coursya.com/product/google-analytics-certification-coursya
8. Fundamentals of digital marketing
https://skillshop.exceedlms.com/student/collection/654330-digital-marketing?locale=en-GB
9. Python Basics for Data Analysis
https://coursya.com/product/learn-python-basics-for-data-analysis
10. Data Science Foundations
https://grow.google/intl/en_in/
11. Advanced Google Analytics
https://coursera.org/professional-certificates/google-data-analytics
12. Google Cloud Computing Foundations:
https://cloudskillsboost.google/course_templates/153
13. Data, ML, and AI in Google Cloud
https://coursya.com/product/google-cloud-computing-foundations-data-ml-and-ai-in-google-cloud-google-cloud-skills-boost
14. Agile Project Management
https://coursera.org/learn/agile-project-management
15. Google Project Management
https://coursera.org/professional-certificates/google-project-management
https://www.tgoop.com/CodeProgrammer
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Forwarded from Data Science Books
We have just launched a fundraising campaign for the channel to ensure continued quality service
We upload the book via Internet data, and this is expensive for us
Participate and contribute to the donation campaign until the target amount is reached
Members who will contribute to the donation campaign will receive a free subscription to the paid channel and a LinkedIn grant
Donate link:
https://boosty.to/datascienceteam/donate
We upload the book via Internet data, and this is expensive for us
Participate and contribute to the donation campaign until the target amount is reached
Members who will contribute to the donation campaign will receive a free subscription to the paid channel and a LinkedIn grant
Donate link:
https://boosty.to/datascienceteam/donate
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๐ฅFree Certification Courses from Microsoft to try in 2023:
1. Get started with Microsoft data analytics
https://learn.microsoft.com/en-us/training/paths/data-analytics-microsoft
2. Prepare data for analysis with Power BI
https://learn.microsoft.com/en-us/training/paths/prepare-data-power-bi
3. Model data with Power BI
https://learn.microsoft.com/en-us/training/paths/model-data-power-bi
4. Build Power BI visuals and reports
https://learn.microsoft.com/en-us/training/paths/build-power-bi-visuals-reports
5. Data analysis in Power BI
https://coursya.com/product/microsoft-power-bi-data-analyst
6. Visualize data in Power BI
https://coursya.com/product/build-power-bi-visuals-and-reports-training
7. Model data in Power BI
https://coursya.com/product/power-bi-for-beginners-designing-a-data-model
8. Prepare data for analysis
https://coursya.com/product/prepare-data-for-analysis-training
9. Get started with Microsoft data analytics
https://coursya.com/product/get-started-with-microsoft-data-analytics-training
10. Microsoft Certified: Power BI Data Analyst Associate
https://coursya.com/product/microsoft-certified-power-bi-data-analyst-associate-certifications
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1. Get started with Microsoft data analytics
https://learn.microsoft.com/en-us/training/paths/data-analytics-microsoft
2. Prepare data for analysis with Power BI
https://learn.microsoft.com/en-us/training/paths/prepare-data-power-bi
3. Model data with Power BI
https://learn.microsoft.com/en-us/training/paths/model-data-power-bi
4. Build Power BI visuals and reports
https://learn.microsoft.com/en-us/training/paths/build-power-bi-visuals-reports
5. Data analysis in Power BI
https://coursya.com/product/microsoft-power-bi-data-analyst
6. Visualize data in Power BI
https://coursya.com/product/build-power-bi-visuals-and-reports-training
7. Model data in Power BI
https://coursya.com/product/power-bi-for-beginners-designing-a-data-model
8. Prepare data for analysis
https://coursya.com/product/prepare-data-for-analysis-training
9. Get started with Microsoft data analytics
https://coursya.com/product/get-started-with-microsoft-data-analytics-training
10. Microsoft Certified: Power BI Data Analyst Associate
https://coursya.com/product/microsoft-certified-power-bi-data-analyst-associate-certifications
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Basic and Full-text Search with Django and Postgres
https://testdriven.io/blog/django-search/
1โฃ Set up basic search functionality with Q objects
2โฃ Add full-text search with Postgres
3โฃ Sort full-text search results by relevance using stemming, ranking, and weighting
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https://testdriven.io/blog/django-search/
1โฃ Set up basic search functionality with Q objects
2โฃ Add full-text search with Postgres
3โฃ Sort full-text search results by relevance using stemming, ranking, and weighting
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๐ฅ Data science path without complexity (Data Science Roadmap):
๐จโ๐ป Programming:
Python ๐
R ๐
Java โ
SQL ๐
๐ Mathematical foundations:
Statistics ๐
Linear algebra ๐ข
Differentiation and integration
Classification mathematics ๐
๐ Data analysis:
Feature Engineering ๐ ๏ธ
Data Wrangling ๐
Interpretative data analysis (EDA) ๐
๐ค Machine Learning:
Classification ๐ท๏ธ
Regression ๐
Reinforcement Learning ๐ฎ
Deep Learning ๐ง
Dimensionality Reduction ๐
Clustering ๐งฉ
๐ธ๏ธ Collect data from the web:
Beautiful Soup ๐ฒ
Scrapy ๐ท๏ธ
URLLIB ๐
๐ Graphical visualization:
Tableau ๐งฎ
D3.js ๐
Scatter Plot ๐
Power BI ๐
ggplot2 ๐
๐ Get ready to explore the depths of this amazing field with these amazing, free educational resources collected in this repository:
https://github.com/Moataz-Elmesmary/Data-Science-Roadmap
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๐จโ๐ป Programming:
Python ๐
R ๐
Java โ
SQL ๐
๐ Mathematical foundations:
Statistics ๐
Linear algebra ๐ข
Differentiation and integration
Classification mathematics ๐
๐ Data analysis:
Feature Engineering ๐ ๏ธ
Data Wrangling ๐
Interpretative data analysis (EDA) ๐
๐ค Machine Learning:
Classification ๐ท๏ธ
Regression ๐
Reinforcement Learning ๐ฎ
Deep Learning ๐ง
Dimensionality Reduction ๐
Clustering ๐งฉ
๐ธ๏ธ Collect data from the web:
Beautiful Soup ๐ฒ
Scrapy ๐ท๏ธ
URLLIB ๐
๐ Graphical visualization:
Tableau ๐งฎ
D3.js ๐
Scatter Plot ๐
Power BI ๐
ggplot2 ๐
๐ Get ready to explore the depths of this amazing field with these amazing, free educational resources collected in this repository:
https://github.com/Moataz-Elmesmary/Data-Science-Roadmap
https://www.tgoop.com/CodeProgrammer
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