Top 5 Budget-Friendly Deep Learning Books for Beginners (2024)

Discover the top 5 budget-friendly deep learning books for beginners in 2024

Introduction

The world of deep learning is booming, revolutionizing fields from artificial intelligence to healthcare. But for beginners, venturing into this exciting domain can seem intimidating. Often, the biggest hurdle is finding the right resources to kickstart your learning journey. Worry not, aspiring deep learning enthusiasts! This blog post unveils the top 5 most affordable deep learning books for beginners in 2024.

These carefully chosen resources will equip you with the foundational knowledge and practical skills to navigate the fascinating world of deep learning without breaking the bank.

Background: Why Deep Learning Matters

Deep learning, a subset of machine learning, has become the backbone of modern AI technologies.

It involves training artificial neural networks with vast amounts of data, enabling machines to perform tasks like image recognition, speech processing, and even playing complex games.

As industries increasingly adopt AI-driven solutions, understanding deep learning is becoming an essential skill for tech professionals.

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1. Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron (O’Reilly Media)

Aurélien Géron’s comprehensive guide is a fantastic starting point for deep learning beginners. It delves into the fundamentals of machine learning, gradually paving the way for a deep understanding of deep learning concepts. The book doesn’t shy away from practical applications, offering valuable techniques for building intelligent systems using popular Python libraries like Scikit-Learn, Keras, and TensorFlow.

What makes it great for beginners:

  • Gradual Learning Curve: Géron’s masterful approach starts with the basics, ensuring a smooth learning curve for those new to the field.
  • Practical Applications: You’ll not only grasp deep learning concepts but also learn to implement them in real-world scenarios.
  • Focus on Popular Tools: The book utilizes widely used Python libraries, making the transition to coding your own models much easier.

Price: Approximately $40

Buy Now: https://amzn.to/3VuTvHg

2. Deep Learning with Python by François Chollet (Manning Publications)

Written by the creator of Keras, François Chollet, this book offers a hands-on introduction to deep learning using Python. Chollet focuses on the practical aspects of building and training deep learning models. You’ll delve into the intricacies of convolutional neural networks (CNNs) for image recognition, recurrent neural networks (RNNs) for sequence analysis, and even explore the fascinating world of natural language processing (NLP).

What makes it great for beginners:

  • Practical Approach: Get ready to roll up your sleeves and start building deep learning models with clear, step-by-step guidance.
  • Focus on Python: As Python remains the go-to language for deep learning, this book ensures a strong foundation for coding your own projects.
  • Written by an Expert: Learning from the creator of Keras itself provides valuable insights and a unique perspective.

Price: Approximately $50

Buy Now: https://amzn.to/4c8X8tJ

3. Grokking Deep Learning by Andrew Trask (Manning Publications)

If traditional textbooks leave you feeling lost in a sea of technical jargon, then Andrew Trask’s “Grokking Deep Learning” might be your perfect companion. This book takes a unique visual approach, explaining complex deep learning concepts through clear illustrations and metaphors.

By breaking down neural networks and backpropagation into easily digestible chunks, Trask empowers beginners to truly “grok” (understand deeply) the inner workings of deep learning.

What makes it great for beginners:

  • Visual Learning Approach: Complex topics are made accessible through engaging illustrations and metaphors.
  • Focus on Understanding: The book prioritizes building a strong conceptual foundation over overwhelming you with code.
  • Engaging Writing Style: Trask’s conversational writing style makes learning deep learning a fun and enjoyable experience.

Price: Approximately $30

Buy Now:https://amzn.to/3W3S6ZX

4. Introduction to Deep Learning by Aaron Courville, Ian Goodfellow, and Yoshua Bengio (MIT Press)

This offering by Aaron Courville, Ian Goodfellow, and Yoshua Bengio is considered a foundational text in the field of deep learning. While geared slightly more towards a theoretical understanding, it remains a valuable resource for beginners with a strong foundation in mathematics and computer science. The book covers crucial topics like neural networks, gradient descent optimization algorithms, and various deep learning architectures.

What makes it great for beginners (with a strong foundation):

  • Theoretical Underpinnings: Gain a solid grasp of the mathematical and algorithmic principles underlying deep learning.
  • Renowned Authors: Learn from some of the leading minds who have shaped the field of deep learning.
  • Comprehensive Coverage: This book delves deeper into the theoretical aspects compared to other entries on this list.

Price: Approximately $60

Buy Now: https://amzn.to/4ccaxkG

5. TensorFlow Machine Learning Cookbook by Rajesh Khanna and Pradeep Geetha Gopal (Packt Publishing)

For those who learn best by doing, “TensorFlow Machine Learning Cookbook” by Rajesh Khanna and Pradeep Geetha Gopal is a goldmine. This book doesn’t waste time on theory; instead, it dives straight into a collection of practical recipes for building machine learning and deep learning models using TensorFlow, a popular open-source library.

What makes it great for beginners (who like to learn by doing):

  • Hands-on Learning: Get ready to code from the very beginning, with practical recipes that guide you through building models step-by-step.
  • Focus on TensorFlow: Master one of the most powerful and widely used deep learning frameworks in the industry.
  • Practical Applications: Each recipe provides a real-world context, making it easier to understand and apply what you’ve learned.

Price: Approximately $35

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Conclusion

Starting your journey into deep learning doesn’t have to be daunting or expensive. The books listed above offer a range of approaches, from hands-on coding to theoretical foundations, ensuring there’s something for every learning style and budget. Equip yourself with one or more of these resources, and you’ll be well on your way to mastering deep learning in 2024.

Kumar Priyadarshi
Kumar Priyadarshi

Kumar Joined IISER Pune after qualifying IIT-JEE in 2012. In his 5th year, he travelled to Singapore for his master’s thesis which yielded a Research Paper in ACS Nano. Kumar Joined Global Foundries as a process Engineer in Singapore working at 40 nm Process node. Working as a scientist at IIT Bombay as Senior Scientist, Kumar Led the team which built India’s 1st Memory Chip with Semiconductor Lab (SCL).

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