The “You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place” is a wonderful book about Artificial Intelligence. Janelle Shane is the author of this great book. Janelle has been featured in the New York Times, WIRED, Popular Science, The Atlantic, and Slate. She has only made a neural network-written recipe once and discovered that horseradish brownies are about as terrible as you might imagine. You Look Like a Thing and I Love You is a great book for anyone who wants to learn about artificial intelligence.

The “Hands-On Convolutional Neural Networks with TensorFlow: Solve computer vision problems with modeling in TensorFlow and Python” is a great book for those who want to use Convolutional Neural Networks for solving real-world problems. Iffat Zafar, Giounona Tzanidou, Richard Burton, Nimesh Patel, and Leonardo Araujo are the authors of this great book. Convolutional Neural Networks are the most popular architectures used in computer vision apps. This book will guide the readers on how to train machine learning models with TensorFlow.

The “Hands-On Neural Networks with TensorFlow 2.0: Understand TensorFlow, from the static graph to eager execution, and design neural networks” is an excellent book that covers machine learning with a focus on developing neural network-based solutions. Paolo Galeone is the author of this informative book. Paolo Galeone is a computer engineer with strong practical experience. In 2019, Google recognized his expertise by awarding him the title of Google Developer Expert (GDE) in Machine Learning. As a GDE, he shares his passion for machine learning and the TensorFlow framework by blogging, speaking at conferences. In this book, you will learn how to create classifiers, build object detection and semantic segmentation networks. After reading this, you will learn how to apply the new features of TF 2.0 to speed up development. How to use the SavedModel file format to put a model, or a generic computational graph, into production. If you are a developer who wants to get started with machine learning and TensorFlow, then Hands-On Neural Networks with TensorFlow 2.0 is for you.

“The Book of Why: The New Science of Cause and Effect” is an accessible book on the new approach to causality in science. Judea Pearl and Dana Mackenzie are the authors of this science book. Judea Pearl is a professor of computer science at UCLA. He has written numerous science books and also won numerous awards. The Book of Why is about how a new science of cause and effect can be joined to statistics, so a robot with real human-like intelligence can be created. This book tells the story of how classical statistics was separated from cause and effect by its development as a mathematical transformation of observed data. Furthermore, the section in the book treats the subject of climate change shows some of the challenges facing those seeking to truly understand what we know and what we don’t know about this issue. To be honest, it is a must-read, not only for causal inference theorists but more widely for those with an interest in contemporary developments in computer science or Artificial Intelligence. Each topic is covered clearly and concisely and packed with the details that you learn to be truly effective. To sum it up, The Book of Why is an educational book for the readers.

The “Machine Learning for Finance: Principles and practice for financial insiders” is an instructive book that explores new developments in the machine.Jannes Klaasis the author of this informative book. Jannes Klaas is a quantitative researcher with a background in economics and finance. He explains about machine learning for finance as lead developer for machine learning at the Turning society. Jannes is currently a graduate student at Oxford University with active research interests including systemic risk and large scale automated knowledge discovery. In Machine Learning for Finance, is based on machine learning training courses for professionals and provides basics concepts and advanced ML ideas that should be applied in an extensive variety of ways. With the help of this book, you will learn how machine learning can detect fraud, analyze customer sentiments and more. You will also learn about address bias and privacy concerns in machine learning.

The “Introduction to Machine Learning with Python: A Guide for Data Scientists, 1st Edition” is a helpful programming book about Machine learning. Andreas C. Muller and Sarah Guido are the authors of this programming book. Andreas C. Muller received his Ph.D. in machine learning from the University of Bonn. After working on the machine learning researcher on computer vision applications at Amazon for a year, now he recently joined the Center for Data Science at New York University.