BOOKS - PROGRAMMING - Design of Intelligent Applications using Machine Learning and D...
Design of Intelligent Applications using Machine Learning and Deep Learning Techniques - Ramchandra S. Mangrulkar, Antonis Michalas, Narendra M. Shekokar, Meera Narvekar, Pallavi V. Chavan 2021 PDF CRC Press BOOKS PROGRAMMING
ECO~18 kg CO²

1 TON

Views
82366

Telegram
 
Design of Intelligent Applications using Machine Learning and Deep Learning Techniques
Author: Ramchandra S. Mangrulkar, Antonis Michalas, Narendra M. Shekokar, Meera Narvekar, Pallavi V. Chavan
Year: 2021
Pages: 447
Format: PDF
File size: 21,7 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Machine Learning Applications in Non-Conventional Machining Processes
Machine Learning and Data Science Fundamentals and Applications
Machine Learning and IoT Applications for Health Informatics
Machine Learning Applications in Non-conventional Machining Processes
Machine Learning for Healthcare Systems Foundations and Applications
Advances in Smart Healthcare Paradigms and Applications: Outstanding Women in Healthcare-Volume 1 (Intelligent Systems Reference Library, 244)
Analysis and Design of Machine Elements
Machine Design with CAD and Optimization
Machine Elements Life and Design
Machine Design - Innovators 2024
Thermal Energy Systems: Design, Computational Techniques, and Applications (Advances in Manufacturing, Design and Computational Intelligence Techniques)
On-Road Intelligent Vehicles Motion Planning for Intelligent Transportation Systems
Artificial Intelligence and Machine Learning Applications for Sustainable Development
Fundamentals of Supervised Machine Learning With Applications in Python, R, and Stata
Machine Learning for High-Risk Applications (3d Early Release)
Machine Learning for Asset Management New Developments and Financial Applications
An Introduction to Optimization With Applications to Machine Learning, 5th Edition
Data Science and Machine Learning Applications in Subsurface Engineering
Python for Machine Learning From Fundamentals to Real-World Applications
Data Science and Machine Learning Applications in Subsurface Engineering
Applications of Deep Machine Learning in Future Energy Systems
Fundamentals of Supervised Machine Learning With Applications in Python, R, and Stata
Blockchain, Big Data and Machine Learning Trends and Applications
Machine Learning and Analytics in Healthcare Systems Principles and Applications
Cognitive Machine Intelligence Applications, Challenges, and Related Technologies
Python for Machine Learning From Fundamentals to Real-World Applications
Big Data, IoT, and Machine Learning Tools and Applications
Cybernetics, Human Cognition, and Machine Learning in Communicative Applications
Applications of Optimization and Machine Learning in Image Processing and IoT
Applications of Optimization and Machine Learning in Image Processing and IoT
Data Science and Machine Learning Applications in Subsurface Engineering
Hands On Machine Learning with Python Concepts and Applications for Beginners
Real-Time Cloud Computing and Machine Learning Applications
Building Machine Learning Powered Applications (Early Release)
Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch
Applications of Deep Machine Learning in Future Energy Systems
Python for Machine Learning: From Fundamentals to Real-World Applications
Cognitive Machine Intelligence Applications, Challenges, and Related Technologies
Supervised Machine Learning Optimization Framework and Applications with SAS and R
An Introduction to Optimization with Applications in Machine Learning and Data Analytics