Production ML Systems
Acquire the ability to differentiate between static and dynamic training and inference, manage model dependencies, establish distributed training for defect tolerance and replication, and generate exportable models.
Description for Production ML Systems
Level: Advanced
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 18 hours (approximately)
Schedule: Flexible
Pricing for Production ML Systems
Use Cases for Production ML Systems
FAQs for Production ML Systems
Reviews for Production ML Systems
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Production ML Systems
Gain experience creating safe, compliant GCP systems, configuring resources, streamlining procedures, and studying for the Professional Cloud Architect test.
The material equips data engineers to incorporate machine learning models into pipelines while adhering to best practices in collaboration, version control, and artifact management.
A program that emphasizes the practical implementation of data science and machine learning to overcome obstacles through the use of Python.
In-depth study of the applications of machine learning and computer vision, as well as practical experience in data analysis and Python programming.
Acquire the fundamental skills of data management, extraction, querying, and visualization to power your AI initiatives.
This course delves deeply into AI bias, equipping students with the knowledge they need to design responsible and ethical AI systems.
Explores the ethical consequences, practical applications, and varieties of AI systems in education and the workplace.
Acquire actionable insights to effectively formulate and execute AI strategies within your organization.
This specific course emphasizes the integration of machine learning and AI with big data administration, utilizing Google Cloud services.
Offers a wider understanding and practical skills for excelling at machine learning and pursuing research opportunities.
Featured Tools
A practical guide to the use of generative AI for the purpose of composing, refining, and planning, utilizing structured and context-driven inputs.
To enhance machine learning models, this course offers fundamental understanding of artificial intelligence, machine learning methods like classification, regression, and clustering.
Acquire an extensive understanding of reinforcement learning, deep neural networks, clustering, and dimensionality reduction to effectively address real-world machine learning challenges.
Acquire practical expertise in the integration of machine learning models into pipelines, optimizing performance, and efficiently managing versioning and artifacts.
This course covers Python programming, TensorFlow for linear regression, and app development for stock market prediction.
Compare & Review AI Tool Directory AI Course Marketplace
