Machine Learning Fundamentals Course
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Machine Learning Fundamentals Course
This Machine Learning Fundamentals Course provides a comprehensive introduction to the field of machine learning. It covers a wide range of topics, starting with an overview of what machine learning is and its historical development. The course then delves into the basics of machine learning, including data preprocessing, feature engineering, and model evaluation. The course explores both supervised and unsupervised learning techniques, such as linear regression, logistic regression, decision trees, and clustering algorithms. It also covers model optimization and regularization, including cross-validation, hyperparameter tuning, and regularization techniques. One of the highlights of the course is the chapter on neural networks and deep learning, which introduces participants to the fundamentals of neural networks, convolutional neural networks, and recurrent neural networks. The course also covers natural language processing, recommender systems, transfer learning, model deployment, ethical considerations in machine learning, anomaly detection, reinforcement learning, time series analysis, and advanced topics such as ensemble learning and explainable AI. This course provides a solid foundation in machine learning, equipping participants with the necessary knowledge and skills to build and deploy machine learning models in real-world scenarios. Whether you are a beginner or an experienced practitioner, this course offers valuable insights into the fundamental concepts and techniques of machine learning.
Machine Learning Fundamentals
Author: Hui Jiang
language: en
Publisher: Cambridge University Press
Release Date: 2021-11-25
A coherent introduction to core concepts and deep learning techniques that are critical to academic research and real-world applications.
Machine Learning Fundamentals
Author: Dr.Sunil Tekale Mrs. Nandagiri Kiranmai Ms.Nazima Begum Ms. RACHAKONDA M D H LAVANYA Mr. M. Pramod Mr. B.PREM KUMAR
language: en
Publisher: Blue Rose Publishers
Release Date: 2025-03-03
"Machine Learning Fundamentals" offers an accessible and structured approach to understanding the core concepts, algorithms, and techniques that power the field of machine learning. This book is designed for beginners, students, or professionals transitioning into ML, providing both theoretical foundations and practical examples to help readers build a strong understanding of how machine learning works.