Overview
Enroll in the fourth installment of the IBM AI Enterprise Workflow Certification, a course specifically tailored for continuing your journey in artificial intelligence with a focus on Machine Learning, Visual Recognition, and NLP (Natural Language Processing). This crucial course is designed as part of a comprehensive specialization, where each module seamlessly builds upon the last. It's highly recommended to undertake this series in sequence for a coherent and structured learning experience.
In Course 4, dive deep into the crucial phase of the AI workflow relevant for a hypothetical streaming media company. This includes setting up models and configuring the essential data pipelines. Kickstart your learning with a thorough exploration of evaluation metrics to understand the best practices across regression metrics, classification metrics, and multi-class metrics. These insights will aid in determining the most efficient model for addressing various business challenges.
Advance your knowledge with detailed discussions on the optimal practices for several model types such as linear models, tree-based models, and neural networks. Experience hands-on learning with IBM's ready-to-use Watson models for Natural Language Understanding (NLU) and Visual Recognition, bringing practical context to your learning through case studies in NLP and image analysis.
By the end of this course, you will have gained the ability to:
- Analyze and apply common metrics for regression, classification, and multi-label classification,
- Utilize linear and logistic regression in supervised learning,
- Implement grid searching and cross-validation strategies,
- Select models for production based on evaluation metrics,
- Describe the application of tree-based algorithms and Neural Networks in supervised learning,
- Design a neural net model using Tensorflow,
- Create and evaluate Watson Visual Recognition and NLU instances.
This course is particularly beneficial for existing data science professionals looking to enhance their expertise in deploying AI within large enterprises. It presupposes completion of the first three courses in the IBM AI Enterprise Workflow specialization and a robust understanding of linear algebra, statistics, machine learning, Python programming, using IBM Watson Studio, and familiarity with the design thinking process.
Choose this course to deepen your skills in Machine Learning, Visual Recognition, and NLP and pave your way to becoming a more knowledgeable practitioner in the field of AI.
Categories: Machine Learning Courses, Natural Language Processing (NLP) Courses, Linear Regression Courses, Regression Analysis Courses.
Syllabus
Taught by
Mark J Grover and Ray Lopez, Ph.D.
