Machine Learning Bookcamp

Alexey Grigorev

ISBN 10: 1617296813 / ISBN 13: 9781617296819

Editore: Manning Publications, US, 2021

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The only way to learn is to practice! In   Machine Learning Bookcamp, you'll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you've learned in previous chapters. By the end of the bookcamp, you'll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technologyMachine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that's exactly what you'll be doing in   Machine Learning Bookcamp. about the bookIn   Machine Learning Bookcamp  you'll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you'll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You'll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you're done working through these fun and informative projects, you'll have a comprehensive machine learning skill set you can apply to practical on-the-job problems.   what's inside Code fundamental ML algorithms from scratchCollect and clean data for training modelsUse popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlowApply ML to complex datasets with images and textDeploy ML models to a production-ready environment about the readerFor readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev  has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.

Codice articolo LU-9781617296819

Dati bibliografici

• Titolo: Machine Learning Bookcamp
• Editore: Manning Publications, US
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 1617296813
• ISBN 13: 9781617296819
• Rilegatura: Paperback
• Condizione: New
• Peso: 840 grammi

Descrizione articolo

Riassunto

Time to flex your machine learning muscles! Take on the carefully designed challenges of the Machine Learning Bookcamp and master essential ML techniques through practical application.

Summary
In Machine Learning Bookcamp you will:

    Collect and clean data for training models
    Use popular Python tools, including NumPy, Scikit-Learn, and TensorFlow
    Apply ML to complex datasets with images
    Deploy ML models to a production-ready environment

The only way to learn is to practice! In Machine Learning Bookcamp, you’ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image analysis, each new project builds on what you’ve learned in previous chapters. You’ll build a portfolio of business-relevant machine learning projects that hiring managers will be excited to see.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology
Master key machine learning concepts as you build actual projects! Machine learning is what you need for analyzing customer behavior, predicting price trends, evaluating risk, and much more. To master ML, you need great examples, clear explanations, and lots of practice. This book delivers all three!

About the book
Machine Learning Bookcamp presents realistic, practical machine learning scenarios, along with crystal-clear coverage of key concepts. In it, you’ll complete engaging projects, such as creating a car price predictor using linear regression and deploying a churn prediction service. You’ll go beyond the algorithms and explore important techniques like deploying ML applications on serverless systems and serving models with Kubernetes and Kubeflow. Dig in, get your hands dirty, and have fun building your ML skills!

What's inside

    Collect and clean data for training models
    Use popular Python tools, including NumPy, Scikit-Learn, and TensorFlow
    Deploy ML models to a production-ready environment

About the reader
Python programming skills assumed. No previous machine learning knowledge is required.

About the author
Alexey Grigorev is a principal data scientist at OLX Group. He runs DataTalks.Club, a community of people who love data.

Table of Contents

1 Introduction to machine learning
2 Machine learning for regression
3 Machine learning for classification
4 Evaluation metrics for classification
5 Deploying machine learning models
6 Decision trees and ensemble learning
7 Neural networks and deep learning
8 Serverless deep learning
9 Serving models with Kubernetes and Kubeflow

Informazioni sull'autore

Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.