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Practical Full Stack Machine Learning

By Alok Kumar

Practical Full Stack Machine Learning Computer Science

Practical Full Stack Machine Learning

0 - Default Title
Description
Master the ML process, from pipeline development to model deployment in production. KEY FEATURES ¿ Prime focus on feature-engineering, model-exploration & optimization, dataops, ML pipeline, and scaling ML API.¿ A step-by-step approach to cover every data science task with utmost efficiency and highest performance.¿ Access to advanced data engineering and ML tools like AirFlow, MLflow, and ensemble techniques. WHAT YOU WILL LEARN¿ Learn how to create reusable machine learning pipelines that are ready for production.¿ Implement scalable solutions for pre-processing data tasks using DASK.¿ Experiment with ensembling techniques like Bagging, Stacking, and Boosting methods.¿ Learn how to use Airflow to automate your ETL tasks for data preparation.¿ Learn MLflow for training, reprocessing, and deployment of models created with any library.¿ Workaround cookiecutter, KerasTuner, DVC, fastAPI, and a lot more.
WHO THIS BOOK IS FOR This book is geared toward data scientists who want to become more proficient in the entire process of developing ML applications from start to finish. Knowing the fundamentals of machine learning and Keras programming would be an essential requirement. TABLE OF CONTENTS1. Organizing Your Data Science Project2. Preparing Your Data Structure3. Building Your ML Architecture4. Bye-Bye Scheduler, Welcome Airflow5. Organizing Your Data Science Project Structure6. Feature Store for ML 7. Serving ML as API
Product details
Binding:
Paperback
Number of Pages:
424
Release Date:
2021-11-26
Publication Date:
2021-11-26
Publisher:
BPB Publications
Languages:
Original: English
ISBN10:
9391030424
ISBN13:
9789391030421
GPSR Manufacturer Reference:
[email protected]
Weight:
787 g
Height:
191 cm
Width:
235 cm
Thickness:
23 cm
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