Understanding Machine-Learning : From Theory to Algorithms /

-д хадгалсан:

Номзүйн дэлгэрэнгүй
Үндсэн зохиолч:	Shalev-Shwartz, Shai (autor)
Бусад зохиолчид:	Ben-David, Shai (autor) (autor)
Формат:	Ном
Хэл сонгох:	англи
Хэвлэсэн:	Nueva York, EUA : Cambridge University, 2018, c2014
Хэвлэл:	1a edición, 9a reimpresión
Нөхцлүүд:	Aprendizaje Automático (Inteligencia Artificial) - > Tema Principal Inteligencia Artificial Autómatas Matemáticos - > Teoría Algoritmos Computacionales Modelos Matemáticos Programación (Software) Sistemas Computacionales Ingeniería Computacional
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!

Ижил төстэй зүйлс: Understanding Machine-Learning :

Түргэн харуулах
Understanding Machine-Learning : From Theory to Algorithms /
Түргэн харуулах
Machine Learning Algorithms : Popular Algorithms for Data Science and Machine Learning /
Түргэн харуулах
An Introduction to Machine Learning /
Түргэн харуулах
Feature Learning and Understanding : Algorithms and Applications /
Түргэн харуулах
Designing Machine Learning Systems /
Түргэн харуулах
Tree-based Machine Learning Algorithms : Decision Trees, Random Forests, and Boosting /
Түргэн харуулах
Probabilistic Machine Learning : Advanced Topics /
Түргэн харуулах
Optimization and Machine Learning : Optimization for Machine Learning and Machine Learning for Optimization /
Түргэн харуулах
Machine Learning : A Probabilistic Perspective /
Түргэн харуулах
Effective Machine Learning Teams : Best Practices for ML Practitioners /
Түргэн харуулах
Introduction to Generative AI /
Түргэн харуулах
Feature Engineering and Selection : A Practical Approach for Predictive Models /
Түргэн харуулах
Deep Reinforcement Learning in Action /
Түргэн харуулах
Deep Reinforcement Learning Hands-On : Practical Problems of Chatbots, Robotics, Discrete Optimization, Web Automation, and More /
Түргэн харуулах
Feature Engineering Made Easy : Identify Unique Features From Your Dataset in Order to Build Powerful Machine Learning Systems /
Түргэн харуулах
Machine Learning with TensorFlow /
Түргэн харуулах
Feature Engineering for Machine Learning and Data Analytics /
Түргэн харуулах
Mastering Machine Learning with Scikit-Learn : Apply Effective Learning Algorithms to Real-World Problems Using Scikit-Learn /
Түргэн харуулах
Feature Engineering for Machine Learning : Principles and Techniques for Data Scientists /
Түргэн харуулах
Feature Engineering for Machine Learning : Principles and Techniques for Data Scientists /
Түргэн харуулах
Machine Learning and Cybernetics : 13th International Conference Lanzhou, China, July 13–16, 2014 : Proceedings /
Түргэн харуулах
Practical Machine Learning : Tackle the Real-World Complexities of Modern Machine Learning with Innovative and Cutting-Edge Techniques /
Түргэн харуулах
A First Course in Machine Learning /
Түргэн харуулах
From Animals to Animats 13 : 13th International Conference on Simulation of Adaptive Behavior, SAB 2014, Castellón, Spain, July 22-25, 2014 : Proceedings /