Deep Learning Books You Need to Read

Artificial Intelligence (AI) has become an integral part of our lives and work. Deep learning, a subfield of machine learning, neural networks focuses on powerful algorithms inspired by the structure and function of the human brain, known as neural networks.

Most of the advancements in artificial intelligence in recent years have been driven by developments in deep learning. Neural networks are behind applications such as autonomous cars, chatbots, image recognition, and robotics. With the latest developments in generative artificial intelligence, the field of deep learning is more important than ever.

Knowing the theory and application of neural networks is rapidly becoming a necessary step in the learning journey of data scientists and other data professionals. Regardless of your current skill level, you can find the list of 5 essential deep learning books that will help you become an expert in the field here 👇📚.

1. Deep Learning with Python

✍️ Author: François Chollet

📕 Number of Pages: 504

🤔Who is it for: Readers with intermediate programming skills

“Deep Learning with Python” published in 2017 has become a bestselling book in this field. François Chollet, the creator of the popular deep learning framework Keras updated the book in 2021 with more technical information.

Deep Learning with Python, written in a simple style, is an ideal book for learning how to apply neural networks using the TensorFlow and Keras libraries. In the book, you will find illustrations and coding examples. However, you will need intermediate Python knowledge.

The author starts with lessons on artificial intelligence and machine learning, and then provides an in-depth review of the application of deep learning concepts for computer vision, time series, text generation, and more. Towards the end of the book, the author discusses the limitations of deep learning and the future of deep learning.

2. Grokking Deep Learning 

✍️ Author: Andrew W. Trask

📕 Number of Pages: 336

🤔Who is it for: Readers with beginner-level programming skills

Grokking Deep Learning is one of the beginner-friendly books for deep learning. Covering a variety of use cases from image processing to translating texts into different languages, this book is a good choice to start your deep learning journey before moving on to more complex books.

The book combines intuitive theory with coding examples, teaching you how to build neural networks from scratch using only Python and its popular math-supported library NumPy. This book also covers topics like clustering, Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM).

Towards the end of the book, the author also provides a guide on the next steps readers can take to further develop their deep learning skills.

3. Neural Networks and Deep Learning

✍️ Author: Charu C. Aggarwal

📕 Number of Pages: 520

🤔Who is it for: Software engineers, students, researchers

Any list of fundamental deep learning resources would be incomplete without this book. "Deep Learning" written by Goodfellow, Bengio, and Courville is a completely theoretical and in-depth and academic book. It is typically included in the curriculum of deep learning courses at universities around the world.

This 800-page book aims to help students generally enter the fields of machine learning and deep learning. It thoroughly and comprehensively examines the theory and algorithms behind deep learning.

The authors then explore the foundations of applied mathematics and machine learning, including linear, probability, information theory, supervised and unsupervised learning algorithms, Bayesian statistics and more. You can find the free version of the book herehere.

Learn More About Deep Learning 

Deep learning is an important part of the data science toolset. Learning it is a smart move to enhance your career opportunities and create interesting applications.

Books can be a good resource for starting deep learning, but you should also consider other ways of learning. You can check out the following resources that will help you start your deep learning journey.

• Data Science Bootcamps you can check out our.
• You can apply to our data science meet-ups where you can ask questions to expert professionals.
• What is Deep Learning. You can read our article.
• Podcast you can check out our channel.
• Our Newsletter you can subscribe for free.