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<Machine Learning, Fast & Focused!> Completion Challenge

In just 5 weeks, here's what you'll get

  • Supervised and unsupervised learning algorithms, including deep neural networks

  • Intuitive and clear explanations of algorithm and mathematical concepts that capture the essence.

  • Practical techniques for model building, debugging, and evaluation

  • Advanced topics such as ensembles, recommendation systems, and metric learning

Starts Nov 13

34 days

Finish Dec 17

haesunpark님과 함께해요!

24,354

Learners

499

Reviews

132

Answers

4.9

Rating

13

Courses

Although I majored in mechanical engineering, I have worked continuously reading and writing code since graduating. I am a Google AI/Cloud GDE. I run the TensorFlow blog (tensorflow.blog) and explore the fascinating boundary between software and science by writing and translating books about machine learning and deep learning.

book-roadmap.jpg.webp

I have written 『Deep Learning You Study by Building It Yourself』 (Hanbit Media, 2025), 『Self-Study Machine Learning + Deep Learning (Revised Edition)』 (Hanbit Media, 2025), 『Self-Study Data Analysis with Python』 (Hanbit Media, 2023), 『The Art of Conversing with ChatGPT』 (Hanbit Media, 2023), and 『Do it! Introduction to Deep Learning』 (Aegis Publishing, 2019).

『Hands-On Machine Learning with Scikit-Learn and PyTorch』(Hanbit Media, 2026),  『Deep Learning from the Keras Creator (3rd Edition)』(Gilbut, 2026), 『LLM Fine-Tuning, Fast and Focused!』(Insight, 2026), 『LLM & AI with PyTorch』(Hanbit Media, 2026), 『Large Language Models, Fast and Focused!』(Insight, 2025), 『Machine Learning, Fast and Focused!』(Insight, 2025), 『Learn LLMs 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 Course』(Hanbit Media, 2023), 『Hands-On Machine Learning, 3rd Edition』(Hanbit Media, 2023), 『Generative Deep Learning by Building, 2nd Edition』(Hanbit Media, 2023), 『Python That Awakens Your Coding Brain』(Hanbit Media, 2023), 『Natural Language Processing with Transformers』(Hanbit Media, 2022), 『Deep Learning from the Keras Creator, 2nd Edition』(Gilbut, 2022), 『Machine Learning&Deep Learning for Developers』(Hanbit Media, 2022), 『Gradient Boosting with XGBoost and Scikit-Learn』(Hanbit Media, 2022), 『Learn Deep Learning with the Google Brain Team with TensorFlow.js』(Gilbut, 2022), and 『Machine Learning with Python Machine Learning Libraries (2nd Revised Edition)』(Hanbit Media, 2022), among several dozen books translated into Korean.

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Challenge Schedule

  • Recruitment Period: 10/30 (Thu) ~ 11/12 (Wed)

  • Challenge Schedule: 11/13(Thu) ~ 12/17(Wed) (5 weeks)

  • Weekly Reading Amount: Read 2 chapters per week, from Chapter 1 to Chapter 10


  • A certificate of completion will be issued if you complete all missions and reach a 100% course completion rate within the challenge period. If the missions are not completed, a certificate cannot be issued.

  • E-book release date: November 14th; e-books are also included in the book purchase verification.

Challenge Benefits

  • Free coupon for the <Machine Learning, Just the Essentials!> course (valued at 40,000 KRW)


  • <Learning LLMs by Building from Scratch> Course (https://inf.run/wQDh8) 50% discount coupon provided (worth 30,000 KRW)

  • Additional benefits upon completion of the challenge

    • Free coupon for the <Large Language Models, Fast & Focused!> course (valued at 40,000 KRW) (Scheduled to be issued after December 17th)

    • <LLM Fine-tuning, Just the Essentials Fast!> (To be published) Challenge free coupon provided (20,000 KRW value) (Challenge opening and free coupon issuance schedule to be announced later)

  • Benefits are provided as Inflearn coupons. Please be sure to refer to the precautions below.

<Precautions> Must Read!!!

  • On November 13th, the free coupon issuance link for the <Machine Learning, Fast & Core!> course and the 50% discount coupon issuance link for the <Learning LLM by Building from Scratch> course will be sent to challenge participants via the email registered on Inflearn.

  • Please check in advance if you can receive emails from Inflearn. If the email is marked as spam, we will not be able to re-issue it later. If you have any issues receiving emails from Inflearn, please contact the Inflearn Help Desk.

  • The validity period of this link is 3 days. You must issue your free and discount coupons through the link within 3 days. After 3 days, the link will become invalid and you will not be able to issue the coupons!

  • The issued coupons must be used within 1 day!

  • Upon completion of the challenge, a free coupon link for the "Large Language Models, Fast & Core!" course will be sent to your email immediately. Additionally, a free coupon link will be emailed to you when the challenge for the upcoming book "LLM Fine-Tuning, Fast & Core!" (to be published) opens. The methods for issuing and using the coupons are the same as described above.

About the Book

Less complex theory, more essential core concepts!

The most concise guide to mastering machine learning

This book is a bestseller translated into 11 languages and used as a textbook in thousands of universities worldwide, explaining machine learning in a concise and clear manner. It covers everything from basic mathematical concepts to core algorithms, deep learning, and neural networks step-by-step, providing a complete toolkit for solving modern machine learning problems such as clustering, topic modeling, metric learning, and recommendation systems. By connecting theory with practical implementation focusing on essential industry skills, it allows anyone to learn quickly and effectively.

Based on extensive practical experience, the author explains techniques that can be directly applied to real-world projects, such as feature engineering, regularization, handling imbalanced datasets, ensembles, and model evaluation. Composed of intuitive explanations and examples rather than being bogged down by complex formulas, it is useful for everyone from beginners who want to build a solid foundation to practitioners looking to expand their professional capabilities.

Purchase

Reviews

“It is remarkable to have covered such a wide range of topics in just about 100 pages. While most thin books omit the mathematics, this book does not. I also truly loved how it clearly explains core concepts in short sentences. This book is useful for beginners and also helpful for experienced practitioners who need a broad overview.”
- Aurélien Géron (Senior AI Engineer, Author of 《Hands-On Machine Learning》)

“Andriy attempted the impossible task of summarizing the entirety of machine learning in about 100 pages, and he has done an excellent job of selecting both theoretical and practical content useful for practitioners. This book will provide a great foundation as an introductory guide for readers new to machine learning.”
- Peter Norvig (Research Director at Google, co-author of the world-renowned AI textbook AIMA)

Purchase Book

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2025년 11월 12일 오후 03:00

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2025년 12월 17일 오후 02:59

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All

66 lectures

Course Materials:

Recommended for
these people

Who is this course right for?

  • Those who are learning machine learning for the first time

  • Those who want to learn everything from linear regression and logistic regression to ensemble and neural network theories.

  • Those who want to review the machine learning algorithms they learned previously

  • Those who need a solid understanding of machine learning theory

Reviews

All

20 reviews

4.8

20 reviews

  • creatingevery님의 프로필 이미지
    creatingevery

    Reviews 14

    ∙

    Average Rating 5.0

    5

    100% enrolled

    It still seems difficult for me. I'll review it again. Thank you.

    • haesunpark
      Instructor

      Cheer up. You can do it!

  • calculator님의 프로필 이미지
    calculator

    Reviews 297

    ∙

    Average Rating 4.9

    5

    100% enrolled

    Thank you.

    • bluesds9742님의 프로필 이미지
      bluesds9742

      Reviews 2

      ∙

      Average Rating 5.0

      5

      30% enrolled

      It feels like difficult content has been organized in an easy-to-understand way.

      • haesunpark
        Instructor

        I'm glad it was easy to understand. Thank you!

    • galaxia999님의 프로필 이미지
      galaxia999

      Reviews 12

      ∙

      Average Rating 5.0

      5

      63% enrolled

      The book was somewhat difficult to read alone, but the lectures were well understood.

      • bongwoochoi님의 프로필 이미지
        bongwoochoi

        Reviews 3

        ∙

        Average Rating 5.0

        5

        100% enrolled

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