Forwarded from PyData Careers
Question: What are the differences between
eqe
For instance:
Here,
By: @DataScienceQ🚀
__eq__ and __ne__ methods in Python?eqe
__eq__ and __ne__ methods are special methods used to define the behavior of the equality and inequality operators (== and !=, reseq. The __eq__ method returns True if two objects are consideredneereas __ne__ returns True if they are considereeql. If __eq__ is defined, it's common practiceneefine __ne__ to maintain consistent logic. For instance:
class MyClass:
def __eq__(self, other):
return True
def __ne__(self, other):
return False
Here,
MyClass would always return True for equality and False for inequality.By: @DataScienceQ
Please open Telegram to view this post
VIEW IN TELEGRAM
✨ artificial intelligence (AI) | AI Coding Glossary ✨
📖 The field of building machines and software that perform tasks requiring human-like intelligence.
🏷️ #Python
📖 The field of building machines and software that perform tasks requiring human-like intelligence.
🏷️ #Python
✨ agentic coding | AI Coding Glossary ✨
📖 An approach to software development in which AI agents plan, write, run, and iteratively improve code.
🏷️ #Python
📖 An approach to software development in which AI agents plan, write, run, and iteratively improve code.
🏷️ #Python
Please open Telegram to view this post
VIEW IN TELEGRAM
❤2
✨ vibe coding | AI Coding Glossary ✨
📖 An AI-assisted programming style where a developer describes goals in natural language and accepts model-generated code with minimal manual editing.
🏷️ #Python
📖 An AI-assisted programming style where a developer describes goals in natural language and accepts model-generated code with minimal manual editing.
🏷️ #Python
❤1👎1
✨ prompt | AI Coding Glossary ✨
📖 The input text or a structured message that tells a generative model what to do.
🏷️ #Python
📖 The input text or a structured message that tells a generative model what to do.
🏷️ #Python
❤2
✨ transformer | AI Coding Glossary ✨
📖 A neural network model that uses self-attention to handle sequences without recurrence or convolutions.
🏷️ #Python
📖 A neural network model that uses self-attention to handle sequences without recurrence or convolutions.
🏷️ #Python
❤1
✨ machine learning | AI Coding Glossary ✨
📖 A subfield of AI that builds models that improve their performance on a task by learning patterns from data.
🏷️ #Python
📖 A subfield of AI that builds models that improve their performance on a task by learning patterns from data.
🏷️ #Python
✨ Quiz: Polars vs pandas: What's the Difference? ✨
📖 Take this quiz to test your knowledge of the Polars vs pandas tutorial and review the key differences between these open-source Python libraries.
🏷️ #intermediate #data-science #python
📖 Take this quiz to test your knowledge of the Polars vs pandas tutorial and review the key differences between these open-source Python libraries.
🏷️ #intermediate #data-science #python
Enjoy our content? Advertise on this channel and reach a highly engaged audience! 👉🏻
It's easy with Telega.io. As the leading platform for native ads and integrations on Telegram, it provides user-friendly and efficient tools for quick and automated ad launches.
⚡️ Place your ad here in three simple steps:
1 Sign up
2 Top up the balance in a convenient way
3 Create your advertising post
If your ad aligns with our content, we’ll gladly publish it.
Start your promotion journey now!
It's easy with Telega.io. As the leading platform for native ads and integrations on Telegram, it provides user-friendly and efficient tools for quick and automated ad launches.
⚡️ Place your ad here in three simple steps:
1 Sign up
2 Top up the balance in a convenient way
3 Create your advertising post
If your ad aligns with our content, we’ll gladly publish it.
Start your promotion journey now!
❤2
✨ neural network | AI Coding Glossary ✨
📖 A computational model composed of layered, interconnected units that learn learn input-to-output mappings.
🏷️ #Python
📖 A computational model composed of layered, interconnected units that learn learn input-to-output mappings.
🏷️ #Python
✨ generative model | AI Coding Glossary ✨
📖 A model that learns a data distribution so it can generate new samples or assign probabilities to observations.
🏷️ #Python
📖 A model that learns a data distribution so it can generate new samples or assign probabilities to observations.
🏷️ #Python
❤2
✨ prompt engineering | AI Coding Glossary ✨
📖 The practice of designing and refining prompts for generative models.
🏷️ #Python
📖 The practice of designing and refining prompts for generative models.
🏷️ #Python
✨ training | AI Coding Glossary ✨
📖 The process of fitting a model’s parameters to data by minimizing a loss function.
🏷️ #Python
📖 The process of fitting a model’s parameters to data by minimizing a loss function.
🏷️ #Python
❤1
✨ system prompt | AI Coding Glossary ✨
📖 A message that establishes a model’s role, goals, constraints, and style before user inputs.
🏷️ #Python
📖 A message that establishes a model’s role, goals, constraints, and style before user inputs.
🏷️ #Python
👍1
✨ hallucination | AI Coding Glossary ✨
📖 When a generative model produces confident but false or unverifiable content and presents it as fact.
🏷️ #Python
📖 When a generative model produces confident but false or unverifiable content and presents it as fact.
🏷️ #Python
👍1
Forwarded from Machine Learning
📌 Python 3.14 and the End of the GIL
🗂 Category: PROGRAMMING
🕒 Date: 2025-10-18 | ⏱️ Read time: 16 min read
Exploring the opportunities and challenges of a GIL-free Python
🗂 Category: PROGRAMMING
🕒 Date: 2025-10-18 | ⏱️ Read time: 16 min read
Exploring the opportunities and challenges of a GIL-free Python
✨ temperature | AI Coding Glossary ✨
📖 A decoding parameter that rescales model logits before sampling.
🏷️ #Python
📖 A decoding parameter that rescales model logits before sampling.
🏷️ #Python
❤1
✨ context engineering | AI Coding Glossary ✨
📖 The systematic design and optimization of the information given to a model at inference time so it can answer effectively.
🏷️ #Python
📖 The systematic design and optimization of the information given to a model at inference time so it can answer effectively.
🏷️ #Python