Skill Topic · Cinematic

🔨 TF Example 1 Model — Shuffle, Normalize & Build

Aliens School — AI Series #45 W3Schools AI Tutorial se inspired, Hinglish mein! 🚀

Overview

🔨 TF Example 1 Model — Shuffle, Normalize & Build — Quick Facts

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Parameter: Meaning

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sequential(): Layers chain mein (output → next…

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dense: Fully connected layer

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inputShape: [1]: 1 input (Horsepower)

Topic 1

💡 Model Building Steps

📚 ` ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ │ Shuffle │ → │Tensorify │ →…

Topic 2

🔀 Step 1: Shuffle Data

💡 Training se pehle hamesha data shuffle karo! javascript tf.util.shuffle(data); `…

Topic 3

📦 Step 2: Convert to Tensors

🎯 `javascript // Map x values to Tensor inputs const inputs = values.map(obj => obj.x); //…

Topic 4

📊 Step 3: Normalize Data (0-1 Range)

⭐ Neural networks 0-1 range mein best kaam karte hain! `javascript const inputMin =…

Topic 5

🏗️ Step 4: Build the Model

🔑 `javascript const model = tf.sequential(); // Layer 1: Input layer…

Topic 6

⚙️ Step 5: Compile the Model

✨ javascript model.compile({ loss: 'meanSquaredError', optimizer: 'sgd' }); | Setting |…

Topic 7

💻 Complete Model Code

🌟 `javascript // 1. Shuffle tf.util.shuffle(data); // 2. Tensorify const inputs =…

Topic 8

❓ Quiz

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a) Speed ke liye

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b) Model ko varied data milta hai…

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c) File size kam hoti hai

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a) Data delete karna

Quick Quiz

Quiz — Question 1

🔨 TF Example 1 Model — Shuffle, Normalize & Build ka sabse sahi definition kya hai?

Quick Quiz

Quiz — Question 2

🔨 TF Example 1 Model — Shuffle, Normalize & Build ka 'sequential()' kya hai?

Complete! 🎉

🔨 TF Example 1 Model — Shuffle, Normalize & Build Complete!

Aliens School · HIEN · Cinematic Knowledge

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