
Building Machine Learning Pipelines by Hannes Hapke
Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation and TensorFlow Transform Analyze a model in detail using TensorFlow Model Analysis Examine fairness and bias in your model performance Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices Learn privacy-preserving machine learning techniquesHannes Hapke is a VP of Engineering at Caravel, a machine learning company providing novel personalization products for the retail industry. Prior to joining Caravel, Hannes was a Ssenior data science engineer at Cambia Health Solutions, a health solutions provider for 2.6 million people and a machine learning engineer at Talentpair, Inc., where he developed novel deep learning model for recruiting companies. Hannes cofounded a renewable energy startup which applied deep learning to detect homes would be optimal candidates for solar power.Additionally, Hannes has coauthored a publication about natural language processing and deep learning and presented at various conferences about deep learning and Python.
| SKU | Unavailable |
| ISBN 13 | 9781492053194 |
| ISBN 10 | 1492053198 |
| Title | Building Machine Learning Pipelines |
| Author | Hannes Hapke |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | O'Reilly Media |
| Year published | 2020-08-18 |
| Number of pages | 364 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |