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Deep Learning & Machine Learning

Do It! Introduction to Deep Learning

This lecture guides readers to deep learning with the most appropriate pace and straight direction, one step from concept to formula and one step from coding. In addition, there are over 100 graphs, illustrations, and diagrams, so you can easily and quickly accept abstract concepts. Another unique feature of this lecture is that you can start practicing right away by simply accessing a web browser without installing a program. After comfortably understanding the theory, you can directly code and conquer four representative deep learning problems with your eyes, so it is not lacking as a textbook for deep learning. The concepts or terms that you must go over are reviewed twice in the ‘Wait! Let’s move on to the next’ corner in the middle of the text and the ‘Memory Card’ corner at the end of the chapter to increase the learning effect. Let’s quickly overcome deep learning head-on with ‘Do it! Introduction to Deep Learning.’

(4.9) 65 reviews

4,562 learners

  • haesunpark
Deep Learning(DL)
Machine Learning(ML)
Artificial Neural Network

Reviews from Early Learners

What you will learn!

  • Implementing from scratch, from linear regression to deep learning algorithms

  • How deep learning (fully connected neural networks, convolutional neural networks, recurrent neural networks) algorithms work

  • Basic usage of scikit-learn and tensorflow libraries

Let's quickly overcome deep learning head-on by coding honestly!

Lecture Structure📚

01 Introducing Deep Learning
02 Start deep learning with minimal tools.
03 Laying the Foundations of Machine Learning - Numerical Prediction
04 Create a classification neuron - binary classification
05 Learn training know-how
06 Connecting two layers - multilayer neural network
07 Classify multiple items - Multi-classification
08 Classifying images - Convolutional Neural Networks
09 Classifying Text - Recurrent Neural Networks

Recommended for
these people

Who is this course right for?

  • Anyone who wants to implement linear regression and logistic regression algorithms from scratch

  • Anyone who wants to study how deep learning algorithms work

Need to know before starting?

  • Basic linear algebra

  • Numpy

  • Python

Hello
This is

19,407

Learners

183

Reviews

62

Answers

4.8

Rating

4

Courses

기계공학을 전공했지만 졸업 후엔 줄곧 코드를 읽고 쓰는 일을 했습니다. 텐서 플로우 블로그(tensorflow.blog)에 글을 쓰고, 머신러닝과 딥러닝에 관한 책을 집필하고 번역하면서 소프트웨어와 과학의 경계를 흥미롭게 탐험하고 있습니다. 

『챗GPT로 대화하는 기술』(한빛미디어, 2023), 『혼자 공부하는 데이터 분석 with 파이썬』(한빛미디어, 2023),『혼자 공부하는 머신러닝+딥러닝』(한빛미디어, 2020) , 『Do it! 딥러닝 입문』(이지스퍼블리싱, 2019)을 썼습니다.

『코딩 뇌를 깨우는 파이썬』(한빛미디어, 2022), 『트랜스포머를 활용한 자연어 처리』(한빛미디어, 2022), 『케라스 창시자에게 배우는 딥러닝 2판』(길벗, 2022), 『개발자를 위한 머신러닝&딥러닝』(한빛미디어, 2022), 『XGBoost와 사이킷런을 활용한 그레이디언트 부스팅』(한빛미디어, 2022), 『구글 브레인 팀에게 배우는 딥러닝 with TensorFlow.js』(길벗, 2022), 『(개정2판)파이썬 라이브러리를 활용한 머신러닝』(한빛미디어, 2022), 『머신러닝 파워드 애플리케이션』(한빛미디어, 2021), 『파이토치로 배우는 자연어 처리』(한빛미디어, 2021), 『머신 러닝 교과서 3판』(길벗, 2021), 『딥러닝 일러스트레이티드』(시그마프레스, 2021), 『GAN 인 액션』(한빛미디어, 2020), 『핸즈온 머신러닝 2판』(한빛미디어, 2020), 『미술관에 GAN 딥러닝 실전 프로젝트』(한빛미디어, 2019), 『파이썬을 활용한 머신러닝 쿡북』(한빛미디어, 2019)을 포함하여 여러 권의 책을 우리말로 옮겼습니다.

Curriculum

All

22 lectures ∙ (10hr 16min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

65 reviews

4.9

65 reviews

  • kate2236e님의 프로필 이미지
    kate2236e

    Reviews 9

    Average Rating 5.0

    5

    77% enrolled

    딥러닝 처음 공부해보는데 기초부터 차근차근 알려주셔서 너무 좋았습니다!! 감사합니다~!!!

    • 박해선
      Instructor

      도움이 되셨다니 다행입니다. 감사합니다! :)

  • Virus PK님의 프로필 이미지
    Virus PK

    Reviews 2

    Average Rating 5.0

    5

    100% enrolled

    기본적인 개념을 잘 배웠습니다.. 그래도 몇번은 더 봐야 될듯합니다. ^^ 퐈이팅!!!

    • 박해선
      Instructor

      네, 파이팅입니다! :-)

  • cradia3512님의 프로필 이미지
    cradia3512

    Reviews 4

    Average Rating 5.0

    5

    14% enrolled

    내용이 알찹니다!

  • 김세현님의 프로필 이미지
    김세현

    Reviews 1

    Average Rating 4.0

    4

    23% enrolled

    • 우쿠렐레Seungmin님의 프로필 이미지
      우쿠렐레Seungmin

      Reviews 3

      Average Rating 4.3

      5

      100% enrolled

      박해선 선생님덕분에 딥러닝에 입문할 수 있었습니다~!

      • 박해선
        Instructor

        덕담 남겨 주셔서 감사합니다! :)

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