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
82377

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:

Applications of Fuzzy Theory in Applied Sciences and Computer Applications
Paints: Types, Components and Applications (Chemistry Research and Applications)
Applications of Fuzzy Theory in Applied Sciences and Computer Applications
Machine Learning The Ultimate Guide to Understand Artificial Intelligence and Big Data Analytics. Learn the Building Block Algorithms and the Machine Learning’s Application in the Modern Life
Applications of Computational Intelligence Techniques in Communications (Advances in Manufacturing, Design and Computational Intelligence Techniques)
Statistics for Machine Learning Implement Statistical methods used in Machine Learning using Python
Machine Learning Production Systems Engineering Machine Learning Models and Pipelines
Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)
Introduction to Machine Learning (Adaptive Computation and Machine Learning), 4th Edition
Machine Gun The Development of the Machine Gun From the Nineteenth Century to the Present Day
Machine Learning Interviews Kickstart Your Machine Learning and Data Career (Final)
Machine Learning An In-Depth Beginners Guide into the Essentials of Machine Learning Algorithms
Sewing Machine Reference Tool A Troubleshooting Guide to Loving Your Sewing Machine, Again!
Security for Cloud Native Applications The practical guide for securing modern applications using AWS, Azure, and GCP
Security for Cloud Native Applications The practical guide for securing modern applications using AWS, Azure, and GCP
Persistence Best Practices for Java Applications: Effective strategies for distributed cloud-native applications and data-driven modernization
Artificial Intelligence and Industrial Applications: Algorithms, Techniques, and Engineering Applications (Lecture Notes in Networks and Systems, 772)
Machine Learning for Beginners A Complete and Phased Beginner’s Guide to Learning and Understanding Machine Learning and Artificial Intelligence Algoritms
Building Data-Driven Applications with LlamaIndex: A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications
Practical Machine Learning with R and Python Machine Learning in Stereo, Third Edition
Machine Learning for Beginners An Introduction to Artificial Intelligence and Machine Learning
Machine Learning Interviews: Kickstart Your Machine Learning and Data Career
Bread Machine Cookbook 50+ Amazingly Delicious Bread Machine Recipes
Multiple Criteria Decision-Making Methods: Applications for Managerial Discretion (De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences, 14)
Ultimate MLOps for Machine Learning Models Use Real Case Studies to Efficiently Build, Deploy, and Scale Machine Learning Pipelines with MLOps
Small Unit Machine Gun Employment: Machine Gun Theory and Tactics for Infantry Squads and Platoons (Special Tactics Manuals Book 7)
Ultimate MLOps for Machine Learning Models Use Real Case Studies to Efficiently Build, Deploy, and Scale Machine Learning Pipelines with MLOps
Machine Learning For Beginners A Math Free Introduction for Business and Individuals to Machine Learning, Big Data, Data Science, and Neural Networks
Hands-On Machine Learning with Scikit-Learn and Scientific Python Toolkits: A practical guide to implementing supervised and unsupervised machine learning algorithms in Python
Unsupervised Machine Learning in Python Master Data Science and Machine Learning with Cluster Analysis, Gaussian Mixture Models, and Principal Components Analysis
Hacker|s Guide to Machine Learning with Python Hands-on guide to solving real-world Machine Learning problems with Scikit-Learn, TensorFlow 2, and Keras
Fundamentals of Machine & Deep Learning A Complete Guide on Python Coding for Machine and Deep Learning with Practical Exercises for Learners (Sachan Book 102)
Machine Learning Hero Master Data Science with Python Essentials Machine Learning with Python Hands-On Guide from Beginner to Expert (Mastering the AI Revolution Book 1)
Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning
Python Machine Learning A Hands-On Beginner|s Guide to Effectively Understand Artificial Neural Networks and Machine Learning Using Python
Python Machine Learning Is The Complete Guide To Everything You Need To Know About Python Machine Learning Keras, Numpy, Scikit Learn, Tensorflow, With Useful Exercises and examples
Ultimate Machine Learning with ML.NET Build, Optimize, and Deploy Powerful Machine Learning Models for Data-Driven Insights with ML.NET, Azure Functions, and Web API
49 Tales of The Thinking Machine (49 detective stories featuring Professor Augustus S. F. X. Van Dusen, also known as and quot;The Thinking Machine and quot;)
Data Science and Machine Learning Interview Questions Using R: Crack the Data Scientist and Machine Learning Engineers Interviews with Ease
Data Science and Machine Learning Interview Questions Using R Crack the Data Scientist and Machine Learning Engineers Interviews with Ease