Feature Engineering For Machine Learning 101

Udemy
Deal Score0
Free $19.99 Redeem Coupon
Deal Score0
Free $19.99 Redeem Coupon

Feature Engineering For Machine Learning 101, Feature Engineering | Machine Learning | Artificial Intelligence | Chat GPT | LLM | generative ai | Manus | Ai Agent.

Description

1. Data Types Demystified

  • Understand Nominal, Ordinal, Interval, and Ratio features.
  • Learn how to visualize and interpret feature types with ease.

2. Speed Up EDA with Manus (AI Tool)

  • Use Manus, an AI-powered assistant, to accelerate your Exploratory Data Analysis.
  • Automatically generate charts, summary statistics, and insights — fast.
  • Let AI help you find patterns and outliers without coding everything manually.

3. Handling Missing Data Like a Pro

  • What missing values are and why they matter.
  • Practical strategies to fill in numerical and categorical gaps.

4. Smart Feature Selection

  • Use ANOVA F-TestChi-Square, and RFE to choose only the most useful features.
  • Build leaner, faster, and smarter models.

5. Feature Engineering with ChatGPT

  • Use ChatGPT prompts to brainstorm and build new features automatically.
  • Accelerate your workflow with AI-powered feature creation — no coding stress!

6. Dimensionality Reduction with PCA

  • Learn what PCA is and when to use it.
  • Reduce complexity while preserving the most important data patterns.

Why This Course?

  • Designed for absolute beginners (no advanced math or ML required)
  • Visual, simple, and intuitive teaching style
  • Real datasets, hands-on practice
  • Includes cutting-edge AI tools (ChatGPT, Manus)

You’ll Walk Away With:

  • A complete toolkit for transforming raw data into powerful model inputs.
  • Working knowledge of feature selection, missing data handling, PCA, and more.
  • Experience using AI tools like Manus and ChatGPT to save time and boost creativity.
  • Confidence to tackle any ML project with cleaner, smarter data.

Who this course is for:

  • Beginners in Data Science and Machine Learning
  • spiring Machine Learning Practitioners:
  • Anyone Curious About Data
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