9781788622226_pstrongGet more from your data by creating practical machine learning systems with Python/strong/ph4Key Features/h4ulliDevelop your own Python-based machine learning system/liliDiscover how Python offers multiple algorithms for modern machine learning systems/liliExplore key Python machine learning libraries to implement in your projects/li/ulh4Book Description/h4pMachine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems./ppUsing machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. Youll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, youll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems./ppBy the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks./ph4What you will learn/h4ulliBuild a classification system that can be applied to text, images, and sound/liliEmploy Amazon Web Services (AWS) to run analysis on the cloud/liliSolve problems related to regression using scikit-learn and TensorFlow/liliRecommend products to users based on their past purchases/liliUnderstand different ways to apply deep neural networks on structured data/liliAddress recent developments in the field of computer vision and reinforcement learning/li/ulh4Who this book is for/h4pBuilding Machine Learning Systems with Python is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. You will use Pythons machine learning capabilities to develop effective solutions. Prior knowledge of Python programming is expected./p(*_*)9781788622226_

Get more from your data by creating practical machine learning systems with Python

Key Features

Develop your own Python-based machine learning system
Discover how Python offers multiple algorithms for modern machine learning systems
Explore key Python machine learning libraries to implement in your projects

Book Description

Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems.

Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. Youll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, youll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems.

By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks.

What you will learn

Build a classification system that can be applied to text, images, and sound
Employ Amazon Web Services (AWS) to run analysis on the cloud
Solve problems related to regression using scikit-learn and TensorFlow
Recommend products to users based on their past purchases
Understand different ways to apply deep neural networks on structured data
Address recent developments in the field of computer vision and reinforcement learning

Who this book is for

Building Machine Learning Systems with Python is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. You will use Pythons machine learning capabilities to develop effective solutions. Prior knowledge of Python programming is expected.

...(*_*)9781788622226_

Build intelligent end-to-end machine learning systems with Python

Key Features

Use scikit-learn and TensorFlow to train your machine learning models
Implement popular supervised and unsupervised machine learning algorithms in Python
Discover best practices for building production-grade machine learning systems from scratch

Book Description

Machine learning enables systems to make predictions based on historical data. Python is one of the most popular languages used to develop machine learning applications, thanks to its extensive library support. This updated third edition of Building Machine Learning Systems with Python helps you get up to speed with the latest trends in artificial intelligence (AI). With this guide’s hands-on approach, you’ll learn to build state-of-the-art machine learning models from scratch. Complete with ready-to-implement code and real-world examples, the book starts by introducing the Python ecosystem for machine learning. You’ll then learn best practices for preparing data for analysis and later gain insights into implementing supervised and unsupervised machine learning techniques such as classification, regression and clustering. As you progress, you’ll understand how to use Python’s scikit-learn and TensorFlow libraries to build production-ready and end-to-end machine learning system models, and then fine-tune them for high performance. By the end of this book, you’ll have the skills you need to confidently train and deploy enterprise-grade machine learning models in Python.

What you will learn

Build a classification system that can be applied to text, images, and sound
Solve regression-related problems using scikit-learn and TensorFlow
Recommend products to users based on their previous purchases
Explore different methods of applying deep neural networks to your data
Understand recent advances in computer vision and natural language processing (NLP)
Deploy Amazon Web Services (AWS) to run data models on the cloud

Who this book is for

This book is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. Prior knowledge of Python programming is expected.

Filtros

Luis Coelho