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Deep Learning with Excel

Let's visually learn the principles of deep learning using Excel.

(4.7) 15 reviews

501 learners

  • hjk1000
딥러닝
엑셀
Excel
Deep Learning(DL)
VBA

Reviews from Early Learners

What you will learn!

  • Deep Learning Basics

  • Excel Usage

Let's learn the basics of deep learning using Excel.

Deep learning, a core component of artificial intelligence technology, is a model capable of autonomously learning and predicting patterns within complex data. However, this powerful technology ultimately operates through mathematical calculations and iterative optimization processes. Experiencing this process through hands-on experience provides a much deeper understanding than simply learning the theory. Excel, one of our most familiar tools, allows us to visually represent and directly manipulate formulas and data, making it an ideal tool for experiencing the deep learning learning process.

The purpose of this lesson is to implement directly in Excel how a deep learning model processes input data, calculates the difference between the predicted result and the actual value, and then adjusts the parameters to reduce this error. To do this, we will first start with the simplest form of deep learning model, the linear regression model. For example, the output value yyy follows the formula y=wx+by = wx + by=wx+b for the input value xxx, or y=w1x1+w2x2+by = w_1x_1 + w_2x_2 + by=w1​x1​+w2​x2​+b in multivariate expansion. The difference between the value predicted by this model and the actual value is measured through the 'loss function', and the model's parameters www and bbb are adjusted in a way that minimizes this loss.

This parameter adjustment utilizes an optimization algorithm called "gradient descent." Gradient descent works by calculating the gradient of the loss function and gradually adjusting the parameters based on that gradient. Mathematically, this process involves differentiation and matrix operations, and in deep learning, the "backpropagation" algorithm, which automatically handles this process, is at the core.

In Excel, each step (input, weight multiplication, output calculation, loss calculation, gradient calculation, parameter update) can be configured cell by cell. For example, input values and weights can be entered into separate cells, then multiplied to obtain a predicted value. The loss can then be calculated as the difference between the predicted value and the actual value. The gradient can then be calculated based on the loss, and the weights can be adjusted based on this, allowing the model to be gradually optimized.

Furthermore, by directly structuring these processes using Excel formulas, you can implement the core logic of deep learning by hand, without the need for frameworks like Python's TensorFlow or PyTorch. This goes beyond simple implementation; it greatly contributes to a deeper understanding of the internal structure and operating principles of deep learning.

In conclusion, we will utilize the familiar tool of Excel to directly implement and visualize core elements of deep learning, including basic concepts, learning structures, loss functions, gradient descent, and backpropagation. This will allow us to go beyond theoretical understanding and gain practical insights and intuition. Let's work through this process step by step and develop a fundamental understanding of deep learning together. Now, let's fully enter the world of deep learning!

Recommended for
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Who is this course right for?

  • Those new to deep learning and curious about its principles

  • Anyone interested in implementing Deep Learning basics using Excel

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1,488

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Answers

4.7

Rating

10

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안녕하세요

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감사합니다.

Curriculum

All

10 lectures ∙ (1hr 25min)

Published: 
Last updated: 

Reviews

All

15 reviews

4.7

15 reviews

  • 원종갑님의 프로필 이미지
    원종갑

    Reviews 3

    Average Rating 4.0

    4

    30% enrolled

    • 멋진
      Instructor

      평가 감사합니다

  • 한상현님의 프로필 이미지
    한상현

    Reviews 1

    Average Rating 5.0

    5

    100% enrolled

    • 멋진
      Instructor

      너무감사합니다!

  • 정호연님의 프로필 이미지
    정호연

    Reviews 59

    Average Rating 5.0

    5

    30% enrolled

    • 멋진
      Instructor

      수강평 너무 감사합니다! 딥러닝 기초를 이해하시는데 도움이 되면 좋겠네요

  • 경규철님의 프로필 이미지
    경규철

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    Average Rating 5.0

    5

    30% enrolled

    • 멋진
      Instructor

      앗 수강평 너무 감사합니다

  • 김효식님의 프로필 이미지
    김효식

    Reviews 1

    Average Rating 5.0

    5

    30% enrolled

    • 멋진
      Instructor

      감사합니다!

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