Forwarded from Learn Python Hub
#MIT has made courses in key CS areas publicly available. #Python, #algorithms, #ML, neural networks, #OS, #databases, #mathematics — all can be completed for free directly on #YouTube.
tags: #courses
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Forwarded from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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Forwarded from Data Analytics
SQL Basics.pdf
102.8 KB
💻 Collection of cheat sheets on SQL
I've gathered for you short and understandable cheat sheets on the main topics:
▶️ Basics of the SQL language;
▶️ JOINs with clear examples;
▶️ Window functions;
▶️ SQL for data analysis.
An excellent set to refresh your knowledge before a job interview or quickly recall the syntax.
tags: #sql #useful
https://t.iss.one/DataAnalyticsX
I've gathered for you short and understandable cheat sheets on the main topics:
▶️ Basics of the SQL language;
▶️ JOINs with clear examples;
▶️ Window functions;
▶️ SQL for data analysis.
An excellent set to refresh your knowledge before a job interview or quickly recall the syntax.
tags: #sql #useful
https://t.iss.one/DataAnalyticsX
❤11
When have you ever needed to add a mathematical description for your function in Python, but found that it takes too much time?
Non-programmers can't easily read Python's logic. However, manually converting it to LaTeX is slow and quickly becomes outdated as the code changes.
latexify_py solves this problem with a single decorator, generating LaTeX directly from your function, so that the mathematics remains readable and always synchronized with the code.
Main features:
• Three decorators for different outputs: expressions, full equations, or pseudocode
• Displays the rendered LaTeX directly in Jupyter cells
• Functions continue to work normally when called
In addition, latexify_py is open source. Install it using
An article about 3 tools that convert Python code to LaTeX: https://bit.ly/3Pw89yP
Run this code: https://bit.ly/4bW2ycE
https://t.iss.one/CodeProgrammer
Non-programmers can't easily read Python's logic. However, manually converting it to LaTeX is slow and quickly becomes outdated as the code changes.
latexify_py solves this problem with a single decorator, generating LaTeX directly from your function, so that the mathematics remains readable and always synchronized with the code.
Main features:
• Three decorators for different outputs: expressions, full equations, or pseudocode
• Displays the rendered LaTeX directly in Jupyter cells
• Functions continue to work normally when called
In addition, latexify_py is open source. Install it using
pip install latexify-pyAn article about 3 tools that convert Python code to LaTeX: https://bit.ly/3Pw89yP
Run this code: https://bit.ly/4bW2ycE
https://t.iss.one/CodeProgrammer
👍7❤4
Please note that the permanent subscription to our Premium channel will be permanently closed in five days.
The cost of a permanent subscription to our premium channel is $35.
The Premium channel contains thousands of books and courses available for free as direct downloadable Telegram files.
Contact me @HusseinSheikho
The cost of a permanent subscription to our premium channel is $35.
The Premium channel contains thousands of books and courses available for free as direct downloadable Telegram files.
Contact me @HusseinSheikho
❤3👍1🎉1
The most complete list of video courses on Computer Science on the internet.
cs-video-courses — 78K+ stars.
MIT.
Stanford University.
University of California, Berkeley.
Harvard University.
Carnegie Mellon University.
Indian Institutes of Technology.
Princeton University.
California Institute of Technology.
Everything is free. All lectures are in video format. Everything is collected in one repository.
Topics:
→ Data structures and algorithms
→ Operating systems
→ Distributed systems
→ Database systems
→ Computer networks
→ Machine learning
→ Deep learning
→ Natural language processing (NLP)
→ Computer vision
→ Computer graphics
→ Security
→ Quantum computing
→ Robotics
→ Blockchain
From beginner level (CS50) to advanced (6.824 Distributed Systems).
The curriculum is free.🤙
https://github.com/Developer-Y/cs-video-courses
https://t.iss.one/CodeProgrammer⚡️
Save & Share & Like🏃♀️
cs-video-courses — 78K+ stars.
MIT.
Stanford University.
University of California, Berkeley.
Harvard University.
Carnegie Mellon University.
Indian Institutes of Technology.
Princeton University.
California Institute of Technology.
Everything is free. All lectures are in video format. Everything is collected in one repository.
Topics:
→ Data structures and algorithms
→ Operating systems
→ Distributed systems
→ Database systems
→ Computer networks
→ Machine learning
→ Deep learning
→ Natural language processing (NLP)
→ Computer vision
→ Computer graphics
→ Security
→ Quantum computing
→ Robotics
→ Blockchain
From beginner level (CS50) to advanced (6.824 Distributed Systems).
The curriculum is free.
https://github.com/Developer-Y/cs-video-courses
https://t.iss.one/CodeProgrammer
Save & Share & Like
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Forwarded from Code With Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
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Selection for those who want to become a certified Claude architect
Useful resources for preparation in one place 👇
• Registration for certification: https://anthropic.skilljar.com/claude-certified-architect-foundations-access-request
• Training (13 free courses):
https://anthropic.skilljar.com
• Cookbook (examples and practices):
https://github.com/anthropics/anthropic-cookbook
• Exam guide:
https://share.google/0eqIbebzRMUt8KTc8
• Practice questions:
https://claudecertifications.com
• MCP documentation:
https://modelcontextprotocol.io
API documentation:
https://docs.anthropic.com
Useful playbook:
https://drive.google.com/file/d/1luC0rnrET4tDYtS7xe5jUxMDZA-4qNf-/view
Useful resources for preparation in one place 👇
• Registration for certification: https://anthropic.skilljar.com/claude-certified-architect-foundations-access-request
• Training (13 free courses):
https://anthropic.skilljar.com
• Cookbook (examples and practices):
https://github.com/anthropics/anthropic-cookbook
• Exam guide:
https://share.google/0eqIbebzRMUt8KTc8
• Practice questions:
https://claudecertifications.com
• MCP documentation:
https://modelcontextprotocol.io
API documentation:
https://docs.anthropic.com
Useful playbook:
https://drive.google.com/file/d/1luC0rnrET4tDYtS7xe5jUxMDZA-4qNf-/view
❤5