Python Machine Learning Blueprints

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 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 go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from 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 you'll 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.

Type
ebook
Category
Data
publication date
2019-01-31
what you will learn

Understand the Python data science stack and commonly used algorithms
Build a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window
Understand NLP concepts by creating a custom news feed
Create applications that will recommend GitHub repositories based on ones you’ve starred, watched, or forked
Gain the skills to build a chatbot from scratch using PySpark
Develop a market-prediction app using stock data
Delve into advanced concepts such as computer vision, neural networks, and deep learning

no of pages
378
duration
756
key features
Get to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and Keras * Implement advanced concepts and popular machine learning algorithms in real-world projects * Build analytics, computer vision, and neural network projects *
approach
A hands-on, project-based approach to teaching the core concepts of machine learning using the most popular tools in the Python
audience
This book is for machine learning practitioners, data scientists, and deep learning enthusiasts who want to take their machine learning skills to the next level by building real-world projects. The intermediate-level guide will help you to implement libraries from the Python ecosystem to build a variety of projects addressing various machine learning domains. Knowledge of Python programming and machine learning concepts will be helpful.
meta description
Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras
short description
Machine Learning (ML) is transforming the way we understand and interact with the world around us. This book is a perfect guide for you to use the Python ecosystem to cover key domains in the machine learning. You will learn to implement advanced concepts and most used machine learning algorithms using complex datasets and optimized techniques.
subtitle
Put your machine learning concepts to the test by developing real-world smart projects
keywords
machine learning, Python, TensorFlow, Keras, deep learning, neural networks
Product ISBN
9781788994170