inflearn logo

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) 73 reviews

4,863 learners

Level Basic

Course period Unlimited

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

Reviews from Early Learners

Reviews from Early Learners

4.9

5.0

kate2236e

77% enrolled

This is my first time studying deep learning, and it was great that you taught me step by step from the basics!! Thank you~!!!

5.0

Virus PK

100% enrolled

I learned the basic concepts well.. but I think I need to watch it a few more times. ^^ Fighting!!!

5.0

cradia3512

14% enrolled

The content is informative!

What you will gain after the course

  • 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 haesunpark

22,733

Learners

392

Reviews

131

Answers

4.9

Rating

10

Courses

I majored in mechanical engineering, but since graduation, I have been consistently reading and writing code. I am a Google AI/Cloud GDE and a Microsoft AI MVP. I run the TensorFlow blog (tensorflow.blog) and am interestingly exploring the boundaries between software and science by writing and translating books on machine learning and deep learning.

 

ml-dl-book-roadmap.png.webp

 

He has authored "Deep Learning from Scratch" (Hanbit Media, 2025), "Machine Learning + Deep Learning Alone (Revised Edition)" (Hanbit Media, 2025), "Data Analysis with Python Alone" (Hanbit Media, 2023), "The Art of Conversing with ChatGPT" (Hanbit Media, 2023), and "Do it! Introduction to Deep Learning" (Easys Publishing, 2019).

 

He has translated dozens of books into Korean, including "Large Language Models: Fast Track to the Core!" (Insight, 2025), "Machine Learning: Fast Track to the Core!" (Insight, 2025), "Learning LLMs by Building from Scratch" (Gilbut, 2025), "Hands-On LLMs" (Hanbit Media, 2025), "Machine Learning Q & AI" (Gilbut, 2025), "Mathematics for Developers" (Hanbit Media, 2024), "Machine Learning Pocket Reference with Python" (Hanbit Media, 2024), "Machine Learning with PyTorch and Scikit-Learn" (Gilbut, 2023), "What Is ChatGPT Doing ... and Why Does It Work?" (Hanbit Media, 2023), "Hands-On Machine Learning, 3rd Edition" (Hanbit Media, 2023), "Generative Deep Learning, 2nd Edition" (Hanbit Media, 2023), "Python for the Coding Brain" (Hanbit Media, 2023), "Natural Language Processing with Transformers" (Hanbit Media, 2022), "Deep Learning with Python, 2nd Edition" (Gilbut, 2022), "AI and Machine Learning for Coders" (Hanbit Media, 2022), "Hands-On Gradient Boosting with XGBoost and Scikit-Learn" (Hanbit Media, 2022), "Deep Learning with TensorFlow.js" (Gilbut, 2022), and "Introduction to Machine Learning with Python, 2nd Revised Edition" (Hanbit Media, 2022).

More

Curriculum

All

22 lectures ∙ (10hr 16min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

73 reviews

4.9

73 reviews

  • kate2236e2216님의 프로필 이미지
    kate2236e2216

    Reviews 9

    Average Rating 5.0

    5

    77% enrolled

    This is my first time studying deep learning, and it was great that you taught me step by step from the basics!! Thank you~!!!

    • haesunpark
      Instructor

      I'm glad it helped. Thanks! :)

  • heetae9909님의 프로필 이미지
    heetae9909

    Reviews 3

    Average Rating 5.0

    5

    32% enrolled

    • dskim1097님의 프로필 이미지
      dskim1097

      Reviews 33

      Average Rating 4.9

      5

      32% enrolled

      • viruspae747418님의 프로필 이미지
        viruspae747418

        Reviews 2

        Average Rating 5.0

        5

        100% enrolled

        I learned the basic concepts well.. but I think I need to watch it a few more times. ^^ Fighting!!!

        • haesunpark
          Instructor

          Yes, fighting! :-)

      • seokillsong1929님의 프로필 이미지
        seokillsong1929

        Reviews 2

        Average Rating 5.0

        5

        64% enrolled

        • haesunpark
          Instructor

          Thank you!

      haesunpark's other courses

      Check out other courses by the instructor!

      Similar courses

      Explore other courses in the same field!

      Free