BOOKS - PROGRAMMING - Practical Machine Learning Innovations in Recommendation
Practical Machine Learning Innovations in Recommendation - Ted Dunning, Ellen Friedman 2014 PDF O;kav_1Reilly Media BOOKS PROGRAMMING
ECO~11 kg CO²

1 TON

Views
5149

Telegram
 
Practical Machine Learning Innovations in Recommendation
Author: Ted Dunning, Ellen Friedman
Year: 2014
Pages: 56
Format: PDF
File size: 10,1 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

The Computational Content Analyst Using Machine Learning to Classify Media Messages
MLOps with Ray Best Practices and Strategies for Adopting Machine Learning Operations
The Computational Content Analyst Using Machine Learning to Classify Media Messages
No-Code AI Concepts and Applications in Machine Learning, Visualization, and Cloud Platforms
Responsible AI Designing, Building, and Assessing Machine Learning and AI (Early Release)
The WebGPU Sourcebook High-Performance Graphics and Machine Learning in the Browser
Hands-on TinyML Harness the power of Machine Learning on the edge devices
Math for Programmers 3D graphics, machine learning, and simulations with Python (Final)
Machine Learning for Kids A Project-Based Introduction to Artificial Intelligence
No-Code AI Concepts and Applications in Machine Learning, Visualization, and Cloud Platforms
Python Machine Learning: A Beginner|s Guide to Scikit-Learn
Machine Learning for Financial Risk Management with Python (Early Release)
Time-Series Sales Forecasting And Prediction Using Machine Learning With Tkinter
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction
Time-Series Sales Forecasting And Prediction Using Machine Learning With Tkinter
Artificial Intelligence and Machine Learning An Intelligent Perspective of Emerging Technologies
MLOps with Ray: Best Practices and Strategies for Adopting Machine Learning Operations
Fundamentals and Methods of Machine and Deep Learning Algorithms, Tools, and Applications
Data Science and Machine Learning for Non-Programmers Using SAS Enterprise Miner
Machine Learning Toolbox for Social Scientists: Applied Predictive Analytics with R
Scaling Python with Dask From Data Science to Machine Learning (Final)
Machine Learning Safety (Artificial Intelligence: Foundations, Theory, and Algorithms)
Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python
MATLAB Statistics and Machine Learning Toolbox User’s Guide (R2023b)
Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification
Handbook of Machine Learning for Computational Optimization Applications and Case Studies
Machine Learning with Noisy Labels: Definitions, Theory, Techniques and Solutions
Feature Engineering for Machine Learning Principles and Techniques for Data Scientists
Machine Learning-Based Modelling in Atomic Layer Deposition Processes
Information-Driven Machine Learning Data Science as an Engineering Discipline
Machine Learning Evaluation Towards Reliable and Responsible AI, 2nd Revised Edition
Machine Learning in Multimedia Unlocking the Power of Visual and Auditory Intelligence
Linear Algebra for Data Science, Machine Learning, and Signal Processing
Machine Learning Refined Foundations, Algorithms and Applications. 2nd Edition
Predictive Safety Analytics Reducing Risk through Modeling and Machine Learning
Machine Learning for Sustainable Development (De Gruyter Frontiers in Computational Intelligence, 9)
Machine Learning con Python costruire algoritmi per generare conoscenza
Machine and Deep Learning Using MATLAB: Algorithms and Tools for Scientists and Engineers
Machine Learning and Cryptographic Solutions for Data Protection and Network Security