Machine Learning Visualized
ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy
-
-
5.0 • 3개의 평가
-
출판사 설명
Book of Jupyter Notebooks that implement and mathematically derive machine learning algorithms from first-principles. The output of each notebook is a visualization of the machine learning algorithm throughout its training phase, ultimately converging at its optimal weights.
장르
컴퓨터 및 인터넷
출시일
2025년
9월 2일
언어
EN
영어
길이
69
페이지
출판사
Gavin Hung
판매자
Gavin Hung
크기
2.8
MB
사용자 리뷰
gmqomg
,
Extremely helpful for my ML class
I love how visual and detailed the book is, it’s very easy to follow. Highly recommend for anyone taking machine learning classes and professionals looking to learn for fun after work. Overall very satisfied with this book, lshort and sweet, straight to the point.
Introduction to Artificial Intelligence for Security Professionals
2017년
Automated Machine Learning
2019년
Artificial Intelligence Technology
2022년
Programming Problems: Advanced Algorithms
2013년
Fundamental Approaches to Software Engineering
2023년
Just Enough R: Learn Data Analysis with R in a Day
2017년
Google Machine Learning and Generative AI for Solutions Architects
2024년
Informed Machine Learning
2025년
Machine Learning and Its Application to Reacting Flows
2023년
Hyperparameter Tuning for Machine and Deep Learning with R
2023년
Decoding AI: A Journey Through Machine Learning, Deep Learning, and Generative Models
2024년
Machine Learning
2020년