Gain a broader understanding of the world of machine learning.

Have you ever wondered what machine learning is?
Are you interested in knowing how they fit into daily life?
Have you ever wondered how machine learning can change and benefit your daily life?

For the last couple of years, AI has made huge strides in understanding and solving complex problems. This is largely thanks to the development of deep learning techniques. But what is deep learning? Why is it so powerful? And how do you use it?

Grokking Algorithms will answer all your questions. We start by focusing on the neural network fundamentals and then provide a deeper look at the advanced techniques and layers used today. By the end of this book, you'll know everything there is to know about deep learning!

In this book, you will:

• Discover and take a deep dive into the world of algorithms and how they're used in everyday life.
• Understand the basics of neural networks and machine learning, and then dive into advanced layers of deep learning.
• Discover backpropagation and activation functions.
• Learn about matrices and the matrix relationship.
• Master full, batch, and stochastic gradient descent.
• Understand regularization and batching.
• Learn modeling probabilities and non-linearities.
• Discover automatic optimization.

This book is perfect for anyone who wants to get started with deep learning or machine learning, but has struggled with understanding it.

Are you interested in learning about the basics of neural networks? Or do you want to take your knowledge of advanced layers to the next level?

Having a guide at your hand to build up your understanding of algorithms and data structures from scratch and how they can come together to create some of the most intricate structures that run the world today will allow you to look at these concepts in an entirely new light!

In this book, you will:

• Learn the importance of data structures and why they're needed today.
• Understand what linear and non-linear data structures are and how they differ from one another.
• Get to know all the different types of linear and non-linear data structures.
• Master all the primitive data types and learn how they can come together to create entirely new data types and data structures.
• Learn how to analyze algorithms.
• Learn how to design algorithms by yourself.
• Learn what advanced search algorithms are and how they can be created.
• Learn what sorting algorithms are and learn how they can be created.
• Get an introduction to scheduling algorithms and their importance.
• Get a basic introduction to the concept of randomness and random algorithms and learn how they can be used to enhance procedures.