Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover the key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects.
The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you'll learn how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you'll cover projects in domains such as predictive analytics to analyze the stock market, and recommendation systems for GitHub repositories. In addition to this, you'll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you'll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and even create an application using computer vision and neural networks.
By the end of this book, you'll be able to analyze data seamlessly and make a powerful impact through your projects.
