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Logistic Regression with NumPy and Python
Coursera Project Network

Logistic Regression with NumPy and Python

Taught in English

Snehan Kekre

Instructor: Snehan Kekre

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Guided Project

Learn, practice, and apply job-ready skills with expert guidance

Beginner level

Recommended experience

1.5 hours
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
4.5

(390 reviews)

What you'll learn

  • Implement the gradient descent algorithm from scratch

  • Perform logistic regression with NumPy and Python

  • Create data visualizations with Matplotlib and Seaborn

Details to know

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Guided Project

Learn, practice, and apply job-ready skills with expert guidance

Beginner level

Recommended experience

1.5 hours
Learn at your own pace
No downloads or installation required
Only available on desktop
Hands-on learning
4.5

(390 reviews)

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  • Gain hands-on experience solving real-world job tasks
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About this Guided Project

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introduction and Project Overview

  2. Load the Data and Import Libraries

  3. Visualize the Data

  4. Define the Logistic Sigmoid Function 𝜎(𝑧)

  5. Compute the Cost Function 𝐽(𝜃) and Gradient

  6. Cost and Gradient at Initialization

  7. Implement Gradient Descent

  8. Plotting the Convergence of 𝐽(𝜃)

  9. Plotting the Decision Boundary

  10. Predictions Using the Optimized 𝜃 Values

Recommended experience

Prior programming experience in Python and machine learning theory is recommended.

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Instructor

Instructor ratings
4.5 (15 ratings)
Snehan Kekre
Coursera Project Network
37 Courses184,534 learners

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How you'll learn

  • Skill-based, hands-on learning

    Practice new skills by completing job-related tasks.

  • Expert guidance

    Follow along with pre-recorded videos from experts using a unique side-by-side interface.

  • No downloads or installation required

    Access the tools and resources you need in a pre-configured cloud workspace.

  • Available only on desktop

    This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.

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4.5

390 reviews

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