Machine Learning Algorithms in Depth

📚📚 I. THÔNG TIN SẢN PHẨM
📒 Mã sản phẩm :  STT1181
📒 Nhà xuất bản :  ‎ ‎ ‎ Manning (August 27, 2024)
📒 Tác giả :      Vadim Smolyakov
📒 ISBN      : 1633439216
📒 Số trang : 328 trang
📒 Hình thức : Bìa Mềm, in ĐEN TRẮNG 
📒 Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
📒 Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và hightlight thoải mái.
📒 Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.

📚📚 II. MÔ TẢ SẢN PHẨM
📒 1.Mô tả sản phẩm

Learn how machine learning algorithms work from the ground up so you can effectively troubleshoot your models and improve their performance.

Fully understanding how machine learning algorithms function is essential for any serious ML engineer. In Machine Learning Algorithms in Depth you’ll explore practical implementations of dozens of ML algorithms including:

• Monte Carlo Stock Price Simulation
• Image Denoising using Mean-Field Variational Inference
• EM algorithm for Hidden Markov Models
• Imbalanced Learning, Active Learning and Ensemble Learning
• Bayesian Optimization for Hyperparameter Tuning
• Dirichlet Process K-Means for Clustering Applications
• Stock Clusters based on Inverse Covariance Estimation
• Energy Minimization using Simulated Annealing
• Image Search based on ResNet Convolutional Neural Network
• Anomaly Detection in Time-Series using Variational Autoencoders

Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probabilistic algorithms, you’ll learn the fundamentals of Bayesian inference and deep learning. You’ll also explore the core data structures and algorithmic paradigms for machine learning. Each algorithm is fully explored with both math and practical implementations so you can see how they work and how they’re put into action.

📒 2. Tác giả
Vadim Smolyakov is a data scientist in the Enterprise & Security DI R&D team at Microsoft. He is a former PhD student in AI at MIT CSAIL with research interests in Bayesian inference and deep learning. Prior to joining Microsoft, Vadim developed machine learning solutions in the e-commerce space.