Practical Full Stack Machine Learning (Alok Kumar) (Z-Library)

Author： Alok Kumar

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. DESCRIPTION 'Practical Full-Stack Machine Learning' introduces data professionals to a set of powerful, open-source tools and concepts required to build a complete data science project. This book is written in Python, and the ML solutions are language-neutral and can be applied to various software languages and concepts. The book covers data pre-processing, feature management, selecting the best algorithm, model performance optimization, exposing ML models as API endpoints, and scaling ML API. It helps you learn how to use cookiecutter to create reusable project structures and templates. It explains DVC