Machine learning/AI Training Overview
Machine learning is based on algorithms that can learn from data without relying on rules-based programming. It came into its own as a scientific discipline in the late 1990s as steady advances in digitization and cheap computing power enabled data scientists to stop building finished models and instead train computers to do so. The unmanageable volume and complexity of the big data that the world is now swimming in have increased the potential of machine learning-and the need for it.
Machine learning/AI Training Course duration
Machine learning/AI Training Course Topics
Machine learning/AI Training Course Objectives
- Overview, goals, learning types, and algorithms
- Data selection, preparation, and modeling
- Model evaluation, validation, complexity, and improvement
- Model performance and error analysis
- Unsupervised learning, related fields, and machine learning in practice
Gain Insights Into These Vital Issues:
Machine learning/AI Training Course outline
- How are traditional industries using machine learning to gather fresh business insights?
- What does it take to get started?
- What's the role of top management?
- Discovering the ambition for the business based on where value is migrating
- Designing a transformation program that targets profitable customer journeys
- Delivering the change through an ecosystem of partners
- De-risking the transformation process to maximize the chances of success
- Where the business should go?
- Create a plan for the digital transformation
- Who will lead the effort?
- How to 'sell' the vision to key stakeholders
- Where to position the firm within the digital ecosystem
- How to decide during the transformation
- Execute the transformation plan, allowing for ongoing adaptation and adjustment.
- How to allocate funds rapidly and dynamically
- Increase the transformation's prospects for success
- How to hire and develop the right team for you
Applicationsof Machine Learning Customized For Your Industry
- Data mining
- Product Search
- Product Recommendation and Promotions
- Trend forecasting and analytics
- Fraud detection and prevention
- Named-entity recognition
- Object Recognition
- Natural-Language Processing
- Machine Vision