Production ML Systems

(0 reviews)

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.

Key AI Functions:Machine Learning,Google Cloud,dynamic training

Description

Reviews

Alternative Tools

Description for Production ML Systems

Contrast static and dynamic training and inference.

Oversee the dependencies of the model

Establish distributed training for the purpose of defect tolerance, replication, and other objectives.

Models that are exportable

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

Reviews for Production ML Systems

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Featured Tools

AGI : An Introductory course

ML Tailored to Marketers

CertNexus Certified AI Practitioner Professional Certificate

Prompt Engineering (ChatGPT)

ML and NLP Basics

Alternative Tools for Production ML Systems

Featured Tools

AGI : An Introductory course

This course provides learners with a comprehensive understanding of AI and AGI, enabling them to participate in and influence the developments that are influencing the future.

#artificial intelligence #data science

ML Tailored to Marketers

Improve targeted marketing, consumer segmentation, and product positioning through the application of machine learning techniques to facilitate more strategic decision-making.

#campaign analysis and testing #predictive analytics in marketing

CertNexus Certified AI Practitioner Professional Certificate

Become an expert in the field of artificial intelligence. Develop effective strategies for the application of Artificial Intelligence techniques to address business challenges.

#Linear Regression #Machine Learning (ML) Algorithms

Prompt Engineering (ChatGPT)

Learn to apply prompt engineering to the effective use of large language models such as ChatGPT, utilize prompt patterns to leverage model capabilities, and develop sophisticated prompt-based applications for diverse contexts such as life, business, or education.

#Prompt Engineering #ChatGPT

ML and NLP Basics

Acquire proficiency in machine learning and deep learning methodologies, such as TensorFlow, CNNs, RNNs, LSTMs, and NLP, to facilitate efficient data analysis.

#tensorflow #machine learning

Compare & Review AI Tool Directory AI Course Marketplace