Fundamentals of Machine Learning a Simplified Approach

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Free Download Fundamentals of Machine Learning: a Simplified Approach
English | 2025 | ISBN: 9789364183444 | 312 pages | EPUB (True) | 1.57 MB
This book aims to serve as a comprehensive introduction to the principles, algorithms, and applications of machine learning, with a particular emphasis on both foundational and cutting-edge techniques. It is designed for students, researchers, and practitioners who wish to deepen their understanding of machine learning concepts, explore their practical applications, and grasp the underlying mathematical frameworks.

The content spans a broad range of topics, beginning with fundamental machine learning concepts, such as regression, decision trees, and artificial neural networks. It then delves into specialized domains like support vector machines, reinforcement learning, and convolutional neural networks. Along the way, readers will encounter detailed explanations of key algorithms, including ID3, Q-learning, and deep Q-learning, as well as practical insights into their implementation. Real-world case studies-such as diabetic retinopathy diagnosis using convolutional neural networks, building smart speakers, and self-driving cars-illustrate the transformative potential of these techniques.


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Machine Learning Fundamentals
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 424 MB | Duration: 1h 20m​

Learn the essentials at a minimum cost!

What you'll learn
Learn about all the basics to start with Machine Learning
Understand the different types of Machine Learning algorithms
Understanding various python libraries used in Machine Learning
A mini project to implement the skills
Learn about supervised and unsupervised machine learning

Requirements
No programming experience needed. All the concepts are taught from basics.
Description
Machine Learning is a key to develop intelligent systems and analyze data in science and engineering. It has emerged as one of the most valuable and time investing domains in the current century. This course is designed for all the learners interested in starting their journey with Machine Learning. The course explains all the important concepts in machine learning. It covers a wide range of topics including types of machine learning, applications and use cases, certifications and job roles.

The course also explains different algorithms in machine learning and a simple mini project with a real life application and implementation. The course will help the learners to clear all the fundamentals and enhance their existing skillset. Machine Learning concepts are implemented using python and basics of all the libraries is also been taught in the course itself. The course is a combination of conceptual theory as well as practical examples and real life project to help the students get ready for your journey.

The key takeaways from the course are

Knowledge about supervised machine learning

Knowledge about unsupervised machine learning

Study of algorithms

Applications of machine learning algorithms

Advantages and disadvantages

Information about the various certifications in the domain

Information about job roles in the domain

Implementation of algorithms in real life project

Who this course is for
Beginner python developers curious to learn machine learning.

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