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

Alexander Turner Verified Buyer – 15/05/2022

The way the book explains algorithms like Decision Trees and Neural Networks is so clear. I finally get it!
Rated 5 out of 5

Sophie Wright Verified Buyer – 12/05/2022

I’ve been wanting to break into AI and ML, but everything I read felt too advanced. This book was the perfect starting point!
Rated 5 out of 5

Theodore Hill Verified Buyer – 11/05/2022

It’s rare to find a book that simplifies ML without dumbing it down. This one strikes the perfect balance!
Rated 5 out of 5

Isabella Green Verified Buyer – 10/05/2022

I had zero experience with coding, but this book still made Machine Learning easy to understand. That’s impressive!
Rated 5 out of 5

Jack Rivera Verified Buyer – 10/05/2022

The writing style is casual but informative. It never feels like a dry textbook, which I really appreciate!
Rated 5 out of 5

Ella Parker Verified Buyer – 27/04/2022

If you’re even slightly curious about Machine Learning, start with this book. It makes everything feel approachable.
Rated 5 out of 5

Henry Taylor Verified Buyer – 26/04/2022

The examples in this book helped me visualize how ML works in the real world. Now I can see how it applies to so many industries!
Rated 5 out of 5

Lucy Young Verified Buyer – 25/04/2022

I’ve read other ML books before, but this one finally made things click for me. Super beginner-friendly!
Rated 5 out of 5

Lucas Hall Verified Buyer – 24/04/2022

I love how this book explains complex ideas in a simple and relatable way. It’s like having a friend walk you through ML concepts!
Rated 5 out of 5

Charlotte Wilson Verified Buyer – 22/04/2022

Before reading this, I thought Machine Learning was only for tech geniuses. Now, I actually feel like I can understand and use it!