Hands-On Machine Learning 2
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.
6,623 learners
Level Basic
Course period Unlimited
"Machine Learning, Just the Essentials, Fast!" and "Large Language Models, Just the Essentials, Fast!" books have been published.
Hello. I'm Park Haeseon.
Are you having a pleasant weekend? 🙂 I have news about a new book publication to share with you.


The Hundred-Page book series written by Andriy Burkov, who led the machine learning team at Gartner, has been published through Insight Publishing! Both <The Hundred-Page Machine Learning Book> and <The Hundred-Page Language Models Book> are bestsellers that gained high popularity on LeanPub and Amazon. These two books have been released as <Machine Learning, Just the Essentials!> and <Large Language Models, Just the Essentials!> respectively.
These two books thoroughly explore the true nature of machine learning and large language models through theory and examples. Although they are relatively thin books of about 200 pages, their style of progressing step by step from basic mathematical theory to reach the summit is remarkably honest and excellently captures the essence. I recommend them to everyone who wants to experience the fundamentals of machine learning and large language models! They are currently available for pre-order at online bookstores. 🙂
Machine Learning, Just the Essentials!: [Kyobo Book Centre] [Yes24] [Aladin]
Large Language Models, Just the Essentials!: [Kyobo Book Centre] [Yes24] [Aladin]
Each
24,0001 won –> 21,600 won
-- P.S.: If you enroll in the <Building and Learning LLM from Scratch> GitHub + bonus content commentary lecture during this week (2025.10.17~2025.10.26), we will randomly select four people to receive
Free




