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@codinginpy

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🚀 Welcome to the new era of learning!
💻 Learn coding through memes.
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⚡ What is cURL Calling?
cURL lets you send requests to APIs directly from your terminal and see their responses.
It helps developers test API endpoints, send data, and debug errors quickly.
Simple flow: Terminal → API Request → Server Response 🚀
Keep learning step by step!

#cURL #APIs #BackendDevelopment #AIEngineering #softwaredevelopment

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AI will do all the work. Why do you even need to learn coding?” 🤡

Me, fighting with 100 errors just to make AI work properly: 😭💀

AI will replace developers? Bro, first let me fix this error! 😂🔥

#AIDeveloper #CodingLife #ProgrammerHumor #Debugging #DeveloperLife

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⚡ Why Do We Use Cache in Applications?

Imagine asking the same question again and again.

That’s where Cache helps.

🔹 Cache → Stores previously used results so they can be returned faster.

🔹 Semantic Cache → Stores results based on the meaning of a query, not just the exact words.

For example:

The words are different, but the meaning is similar. 🧠

A semantic cache can reuse the previous result instead of calling the LLM again.

Cache → Faster response + Less processing ⚡
Semantic Cache → Similar meaning → Reuse result → Save time & cost

Cache is a simple but powerful way to make applications faster and more efficient.

#Caching #SemanticCache #AIEngineering #LLM #GenerativeAI

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Comment to get full pdf

#GitHub #coding #fresher #python #interview
Elyontechminds

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🤖 What is Agentic AI?

AI that can do more than just give answers.

Agentic AI can: 🔹 Understand a goal
🔹 Plan the steps
🔹 Choose the right tools
🔹 Take actions
🔹 Check the results
🔹 Continue until the task is completed

Simple flow:

Goal → Plan → Tool → Action → Check → Result 🚀

Traditional AI mainly responds to prompts.
Agentic AI can work through multiple steps to achieve a goal.

AI is moving from answering questions → taking actions. 🔥

Keep learning. Keep building. Keep exploring AI. 💯

#AgenticAI #AIAgents #ArtificialIntelligence #GenerativeAI #aiengineering

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Python ka naam saanp se nahi, ek comedy show se aaya hai 😱 1989 ki Christmas chhuttiyon mein Guido van Rossum ne ye language banana start kiya tha 🔥
Poori Python history full video mein dekho. Save kar lo, coding journey mein kaam aayega!
#PythonHistory #PythonProgramming #LearnPython #CodingHindi #GuidoVanRossum

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How can we get better answers from AI?

It’s not only about the prompt.

Think about PCM: Prompt + Context + Memory

🔹 Prompt → What do you want AI to do?
🔹 Context → What information does AI need?
🔹 Memory → What relevant information should AI remember?

Simple flow:

Prompt + Context + Relevant Memory → Better AI Output

A clear prompt is important, but the right context and relevant memory can make the response more useful.

Keep learning AI step by step.

#PromptEngineering #ContextEngineering #AI #LLM #GenerativeAI

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🚀 SQL Interview Prep Starts Here!
8 SQL questions every Data Analyst should know 🔥
From JOINs & GROUP BY to Window Functions & CTEs — master the concepts, not just the syntax. 💻📊

#fypppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp #SQLInterview #trandingreels❤️ #fouyou #PowerBI Excel Python Analytics InterviewPrep

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SQL MCQ, SQL quiz, SQL interview questions, SQL query practice, SQL questions, SQL queries, database concepts, learn SQL, SQL interview preparation
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#foryoupage #viralreels #sql #sqlmcq #interviewquestions

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SQL JOINs ko samajhna hai? 🔥
INNER JOIN, LEFT JOIN, RIGHT JOIN & FULL JOIN — real-world examples ke saath! 📊💻
Data Analyst banna hai to SQL JOINs strong karo! 🚀
#SQL #treding #DataAnalyst #fypppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp #PowerBI Excel TechSkills LearnSQL

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Left join with table

#leftjoin
#sql
#database
#datascience
#dataanalytics

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🤖 How do we know if our Machine Learning model is performing well?

That’s where Model Evaluation comes in. 📊

We use different metrics to understand how well our model makes predictions.

🔹 Accuracy → How many predictions are correct
🔹 Precision → How many predicted positives are actually correct
🔹 Recall → How many actual positives are correctly found
🔹 F1 Score → Balance between Precision and Recall
🔹 Confusion Matrix → Shows correct and wrong predictions
🔹 ROC-AUC → Shows how well the model separates classes

For Regression, we can also use MAE and RMSE.

The important thing is: don’t depend on only one metric. Choose the evaluation method based on your problem and data.

Understand the model → Evaluate it → Improve it → Keep learning step by step. 🚀

#ModelEvaluation #MachineLearning #DataScience #AI #ML

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