Machine Learning Explained

Rated 4.95 out of 5 based on 300 customer ratings

$27

ML Fundamentals in-depth
Key Concepts, Algorithms, Data Processing
Applications Across Industries
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About Machine Learning Explained

Introducing our comprehensive guide to Machine Learning for beginners. With this ebook, you will gain a deep understanding of the key concepts and techniques used in modern machine learning.

From supervised and unsupervised learning to deep learning and neural networks, this book covers all the fundamental principles of machine learning. You will also learn about the various algorithms and techniques used in machine learning, and how to evaluate and improve the performance of machine learning models.

This is a limited-time offer!

Introduction to machine learning
What is machine learning and how does it differ from other forms of AI?
1. Other forms of AI
2. Key differences between machine learning and AI
Common applications of machine learning
The basics of machine learning algorithms
Types of data in machine learning
Preparing and preprocessing data for machine learning
Supervised learning algorithms
Unsupervised learning algorithms
Evaluating and improving the performance of machine learning models
Challenges and limitations of machine learning
1. Data quality and quantity
2. Overfitting and underfitting
3. Choosing the right algorithm and hyperparameters
4. Human bias
5. Explainability and interpretability
6. Computational resources
7. Ethical considerations
8. Robustness and generalization
9. Security and privacy
10. Human oversight
11. Ethical considerations
Neural networks and deep learning
Artificial intelligence vs. Machine learning vs. Deep learning
Natural language processing with machine learning
1. Several approaches to NLP with machine learning
Computer vision and image recognition with machine learning
Predictive analytics with machine learning
An introduction to reinforcement learning
Real-world applications of machine learning in various industries
1. Healthcare
2. Finance
3. Retail
4. Manufacturing
5. Transportation
6. Energy
7. Education
8. Cybersecurity
9. Advertising
10. Social media
11. Supply chain management
12. Customer service
13. HR
14. Telecommunications
The Role of Machine Learning in Transforming Industries and Professions
The ethics and social implications of machine learning
1. Bias in data
2. Transparency
3. Privacy
4. Autonomy
5. Social and economic impacts
6. Responsibility and accountability
Machine learning and big data
The role of data visualization in machine learning
Ensemble methods in machine learning
Transfer learning in machine learning
Role of machine learning in shaping society
Integration of machine learning with other technologies
Ethical implications of advanced machine learning systems
1. Bias in machine learning algorithms
2. Uninterpretability of machine learning algorithm
3. Privacy concerns
4. Potential for misuse or abuse of machine learning
5. Need for regulation
Future of machine learning, where we’re heading?
Conclusion

‘…frontrunner in delivering top-tier digital business resources…’

‘…has been making waves with its flagship product…’

‘…consistent emphasis on simplifying complex business topics…’

‘…shaping the future of digital business learning…’

‘…valuable resource in the ever-evolving world of business education…’

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Reviews (300)

300 reviews for Machine Learning Explained

Rated 5 out of 5

Hunter Moore Verified Buyer – 07/07/2022

Unlike other books, this one doesn’t assume you already know a ton about ML. It explains everything from the ground up!
Rated 5 out of 5

Lily Campbell Verified Buyer – 04/07/2022

The visuals and examples in this book made difficult topics so much easier to grasp. It’s a must-read for beginners!
Rated 5 out of 5

Mason Bennett Verified Buyer – 15/06/2022

I love how it explains both the big picture and the small details. It’s perfect for beginners who want a complete introduction!
Rated 5 out of 5

Emily Turner Verified Buyer – 10/06/2022

I used to think AI and ML were all hype, but this book showed me the real impact these technologies have in our daily lives.
Rated 5 out of 5

Owen Anderson Verified Buyer – 04/06/2022

This book answered so many of my beginner questions about AI and ML. I wish I had found it sooner!
Rated 5 out of 5

Lily Robinson Verified Buyer – 03/06/2022

I was skeptical at first, but this book genuinely helped me understand ML instead of just memorizing terms.
Rated 5 out of 5

Mateo Mitchell Verified Buyer – 26/05/2022

If you’re intimidated by Machine Learning, read this book. It turns scary-sounding concepts into something totally doable.
Rated 5 out of 5

Abigail Clark Verified Buyer – 23/05/2022

The step-by-step breakdown of ML processes made it easy to follow along. I never felt lost!
Rated 5 out of 5

Dylan Lewis Verified Buyer – 20/05/2022

The real-world case studies in this book helped me see how ML is shaping the future. It’s more than just theory—it’s practical knowledge!
Rated 5 out of 5

Victoria Martin Verified Buyer – 17/05/2022

I always thought ML was just for software engineers. But this book showed me that it’s relevant to so many fields, even marketing and finance!