inflearn logo
강의

Course

Instructor
inflearn logo
Challenge
Recruitment Upcoming
AI Technology

/

Deep Learning & Machine Learning

[Enterprise Challenge] Machine Learning + Deep Learning for Self-Study

You can learn the foundational knowledge for those learning machine learning and deep learning for the first time. You will cover basic machine learning models such as K-Nearest Neighbors, Linear Regression, Logistic Regression, Decision Trees, and various ensemble algorithms, as well as core concepts for training machine learning models like Stochastic Gradient Descent, regularization, and overfitting/underfitting. It also covers unsupervised learning such as K-Means and PCA. In the deep learning section, you will learn about basic artificial neural networks, deep neural networks, convolutional neural networks, and recurrent neural networks through examples using Keras and PyTorch. The final chapter covers large-scale models based on Transformers. It introduces the structure and core principles of LLMs in detail and helps you acquire practical skills through examples such as summarizing product descriptions or generating answers to questions.

9,061명이 수강한

강의로 진행되는 챌린지!

Machine Learning(ML)
Deep Learning(DL)
B2B Only Challenge

28개 수업 학습

haesunpark님과 함께해요!

23,350

Learners

437

Reviews

131

Answers

4.9

Rating

11

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 enjoy exploring the boundary between software and science by writing and translating books on machine learning and deep learning.

ml-dl-roadmap.png.webp

 He has authored "Deep Learning by Building Alone" (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" (EasysPublishing, 2019).

He has translated dozens of books into Korean, including "LLM Fine-Tuning: Quick Core Concepts!" (Insight, 2026), "Learning LLM & AI with PyTorch" (Hanbit Media, 2026), "Large Language Models: Quick Core Concepts!" (Insight, 2025), "Machine Learning: Quick Core Concepts!" (Insight, 2025), "Learning LLM by Building from Scratch" (Gilbut, 2025), "Hands-On LLM" (Hanbit Media, 2025), "Machine Learning Q & AI" (Gilbut, 2025), "Mathematics for Developers" (Hanbit Media, 2024), "Practical ML Problem Solving with Python" (Hanbit Media, 2024), "Machine Learning Textbook: PyTorch Edition" (Gilbut, 2023), "Stephen Wolfram's ChatGPT Lecture" (Hanbit Media, 2023), "Hands-On Machine Learning, 3rd Edition" (Hanbit Media, 2023), "Generative Deep Learning, 2nd Edition" (Hanbit Media, 2023), "Python for Awakening the Coding Brain" (Hanbit Media, 2023), "Natural Language Processing with Transformers" (Hanbit Media, 2022), "Deep Learning with Python, 2nd Edition" (Gilbut, 2022), "Machine Learning & Deep Learning for Developers" (Hanbit Media, 2022), "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 Edition" (Hanbit Media, 2022).

More

Haesun Park

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

Major Works

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

He has translated dozens of books into Korean, including 『Large Language Models at Work』 (Insight, 2025), 『Machine Learning at Work』 (Insight, 2025), 『Build a Large Language Model (From Scratch)』 (Gilbut, 2025), 『Hands-On Large Language Models』 (Hanbit Media, 2025), 『Machine Learning Q & AI』 (Gilbut, 2025), 『Essential Math for Data Science』 (Hanbit Media, 2024), 『Machine Learning Pocket Reference』 (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), 『The Quick Python Book, 3rd Edition』 (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 Edition』 (Hanbit Media, 2022).

5월

22일

챌린지 시작일

2028년 5월 22일 오후 03:00

챌린지 종료일

2028년 5월 31일 오후 02:30

챌린지 커리큘럼

All

28 lectures

Course Materials:

챌린지 전용 수업

챌린지에서 배워요

  • Machine Learning

  • Deep Learning

  • Scikit-learn

  • TensorFlow

  • Supervised Learning

  • Unsupervised Learning

  • Artificial Neural Network

  • Convolutional Neural Network

  • Recurrent Neural Network

Recommended for
these people

Who is this course right for?

  • Those who want to build a foundation to learn intermediate machine learning and deep learning courses.

  • Those who have hesitated to learn machine learning and deep learning because of difficult theories

  • Those who want to apply it to practice rather than theory

  • Those who want to learn through easy-to-understand explanations rather than mathematics.

Need to know before starting?

  • Python

Reviews

Not enough reviews.
Please write a valuable review that helps everyone!

이 강의의 지난 수강평

취소 및 환불 규정
챌린지는 지식공유자가 설정한 수업 최소 정원이 충족되지 않을 경우, 폐강 안내가 고지되며 결제 내역이 자동취소됩니다.

haesunpark's other courses

Check out other courses by the instructor!

Self-study machine learning + deep learningCourse Thumbnail

Self-study machine learning + deep learning

haesunpark

Free

Basic / Machine Learning(ML), Deep Learning(DL)

4.8

(119)

9,000+

The ultimate machine learning and deep learning tutorial that teaches you like a 1:1 private lesson with Hanbit Media's Honkong series, understand with hundreds of hand drawings, and practice right away with just a browser through Google Colab

Basic

Basic

Machine Learning(ML), Deep Learning(DL)

Self-study machine learning + deep learningCourse Thumbnail

Self-study machine learning + deep learning

haesunpark

Free

Basic / Machine Learning(ML), Deep Learning(DL)

4.8

(119)

9,000+
<From Scratch: Building and Learning LLMs> Commentary LectureCourse Thumbnail

<From Scratch: Building and Learning LLMs> Commentary Lecture

haesunpark

$77.00

Basic / PyTorch, gpt-2, transformer, LLM, Fine-Tuning

4.8

(24)

500+

This is a course covering the GitHub notebooks and bonus content from <Build a Large Language Model from Scratch> (Gilbut, 2025). GitHub: https://github.com/rickiepark/llm-from-scratch/ <Build a Large Language Model from Scratch> is the Korean translation of the bestseller <Build a Large Language Model (from Scratch)> (Manning, 2024) by Sebastian Raschka. This book provides a way to learn and utilize the operating principles of large language models by building a complete model starting from scratch with OpenAI's GPT-2 model.

Basic

Basic

PyTorch, gpt-2, transformer

<From Scratch: Building and Learning LLMs> Commentary LectureCourse Thumbnail

<From Scratch: Building and Learning LLMs> Commentary Lecture

haesunpark

$77.00

Basic / PyTorch, gpt-2, transformer, LLM, Fine-Tuning

4.8

(24)

500+
Hands-On Machine Learning 2Course Thumbnail

Hands-On Machine Learning 2

haesunpark

Free

Basic / Tensorflow, Machine Learning(ML), Deep Learning(DL), Keras, Reinforcement Learning(RL), NLP, Scikit-Learn

4.7

(58)

6,600+

This course covers the content of the Amazon bestseller <Hands-On Machine Learning, 2nd Edition>. You will learn various machine learning algorithms and evaluation methods using Scikit-Learn, a representative machine learning library. Additionally, you will build a foundation in both theory and practice, ranging from artificial neural networks to reinforcement learning, using the most famous deep learning libraries, TensorFlow and Keras. This course is not yet complete. One to two lectures will be added every week.

Basic

Basic

Tensorflow, Machine Learning(ML), Deep Learning(DL)

Hands-On Machine Learning 2Course Thumbnail

Hands-On Machine Learning 2

haesunpark

Free

Basic / Tensorflow, Machine Learning(ML), Deep Learning(DL), Keras, Reinforcement Learning(RL), NLP, Scikit-Learn

4.7

(58)

6,600+
Do It! Introduction to Deep LearningCourse Thumbnail

Do It! Introduction to Deep Learning

haesunpark

Free

Basic / Deep Learning(DL), Machine Learning(ML), Artificial Neural Network

4.9

(80)

4,900+

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.’

Basic

Basic

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

Do It! Introduction to Deep LearningCourse Thumbnail

Do It! Introduction to Deep Learning

haesunpark

Free

Basic / Deep Learning(DL), Machine Learning(ML), Artificial Neural Network

4.9

(80)

4,900+
Python for Waking Up Your Coding BrainCourse Thumbnail

Python for Waking Up Your Coding Brain

haesunpark

Free

Beginner / Python, Pandas

4.9

(15)

900+

Wake up your sleeping coding brain. From Python basics to machine learning, all in one book! Based on MIT lectures, this computer science introductory book is accessible even for beginners with no prior knowledge of programming. Wake up your dormant coding brain with essential introductory topics such as computational thinking and simple algorithms. Through the "Finger Exercise" problems provided in each chapter, you will explore practical subjects like data visualization, simulation, data calculation techniques, and machine learning.

Beginner

Beginner

Python, Pandas

Python for Waking Up Your Coding BrainCourse Thumbnail

Python for Waking Up Your Coding Brain

haesunpark

Free

Beginner / Python, Pandas

4.9

(15)

900+
Large Language Models, Just the Essentials!Course Thumbnail

Large Language Models, Just the Essentials!

haesunpark

$34.10

Beginner / Artificial Neural Network, PyTorch, LLM, Fine-Tuning, RNN

4.7

(10)

100+

This is a lecture covering LLM theory and practical examples based on <Large Language Models, Just the Essentials!> (Insight, 2025).

Beginner

Beginner

Artificial Neural Network, PyTorch, LLM

Large Language Models, Just the Essentials!Course Thumbnail

Large Language Models, Just the Essentials!

haesunpark

$34.10

Beginner / Artificial Neural Network, PyTorch, LLM, Fine-Tuning, RNN

4.7

(10)

100+
Machine Learning, Just the Essentials, Fast!Course Thumbnail

Machine Learning, Just the Essentials, Fast!

haesunpark

$34.10

Beginner / Artificial Neural Network, CNN, linear-regression, RNN, ensembles

4.8

(8)

100+

This is a lecture covering machine learning theory and practical examples based on <Machine Learning, Just the Essentials!> (Insight, 2025).

Beginner

Beginner

Artificial Neural Network, CNN, linear-regression

Machine Learning, Just the Essentials, Fast!Course Thumbnail

Machine Learning, Just the Essentials, Fast!

haesunpark

$34.10

Beginner / Artificial Neural Network, CNN, linear-regression, RNN, ensembles

4.8

(8)

100+

$254.10