AI Workflow: Machine Learning, Visual Recognition and NLP
Master advanced ML techniques including neural networks, visual recognition, and NLP using IBM Watson and TensorFlow.
Master advanced ML techniques including neural networks, visual recognition, and NLP using IBM Watson and TensorFlow.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full IBM AI Enterprise Workflow Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.4
(77 ratings)
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Instructors:
English
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What you'll learn
Implement and evaluate machine learning models using multiple metrics
Develop neural networks using TensorFlow
Utilize IBM Watson for visual recognition and NLP tasks
Apply tree-based methods and ensemble learning
Create production-ready ML pipelines
Skills you'll gain
This course includes:
0.5 Hours PreRecorded video
11 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 2 modules in this course
This comprehensive course covers advanced machine learning techniques focusing on model evaluation, neural networks, and IBM Watson services. Students learn to implement and evaluate various ML models including linear models, tree-based algorithms, and deep learning networks. The curriculum includes hands-on experience with natural language understanding and visual recognition using IBM Watson, culminating in practical case studies involving NLP and image analysis.
Model Evaluation and Performance Metrics
Module 1 · 7 Hours to complete
Building Machine Learning and Deep Learning Models
Module 2 · 6 Hours to complete
Fee Structure
Instructors
Digital Content Delivery Lead at IBM with Extensive Experience in Information Technology Education
Mark J. Grover is a Digital Content Delivery Lead at IBM, specializing in the creation and delivery of online educational content. Before joining IBM, he was a full-time professor of computer technology at Cape Fear Community College in Wilmington, NC, where he coordinated the Information Security program and taught various courses including Computer Security and Network Administration. Grover has over 25 years of experience in information technology and has received accolades such as the Cisco Instructor of Excellence award and the Award for Excellence in Innovation from the University of North Carolina Wilmington. He is passionate about outdoor activities like camping and mountain biking, and enjoys spending time with his family.
Expert in Data Science and AI Education
Ray Lopez, Ph.D., is a prominent technical and educational expert with over 30 years of experience in various fields, including software development, system administration, and technical architecture. He has a strong background in basic research in neuroscience and artificial intelligence, which complements his extensive teaching experience at the university level in subjects such as science, mathematics, statistics, and philosophy. Currently serving as the Data Science Curriculum Leader at IBM, Dr. Lopez is dedicated to developing education and certification programs that enhance skills in data science.His current projects focus on creating comprehensive courses that cover critical aspects of AI workflows, including data analysis, machine learning, and enterprise model deployment. Dr. Lopez's work aims to bridge the gap between business priorities and technical implementations, equipping learners with the necessary tools to succeed in the evolving landscape of data science and AI technologies.
Testimonials
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4.4 course rating
77 ratings
Frequently asked questions
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