- Master essential machine learning concepts and techniques.
- Develop predictive models using machine learning algorithms.
- Analyze and interpret large datasets for insights.
- Implement machine learning solutions in various domains.
- Optimize and fine-tune machine learning models.
- Evaluate and validate the performance of models.
- Apply ethical considerations in machine learning applications.
- Stay updated with the latest machine learning trends.
Syllabus2.Applying Machine Learning to Business Needs:
3.Looking Inside Machine Learning:
- What is Machine Learning
- Iterative learning from data
- What s old is new again
- Definition of Big Data
- Big Data in Context with Machine Learning
- The Need to Understand and Trust your Data
- Hybrid Cloud And Its importance
- Leveraging the Power of Machine Learning
- Descriptive analytics
- Predictive Analytics
- When Statistics and Data Mining Teams Up with Machine Learning
- Machine Learning in Context
- Approaches towards Machine Learning
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Neural networks and deep learning
4.Getting Started With Machine Learning:
- Understanding of customer dissatisfaction
- Recognizing the reason behind poor customer satisfaction
- Preventing Accidents from happening
- Advice for Applying Machine Learning
5.Learning Machine Skills:
- The Impact of Machine Learning on Applications
- Algorithm s role
- Categories of the machine learning algorithm
- Training machine learning systems
- Data Preparation
- Identifying Relevant Data
- Governing Data
- The Machine Learning Cycle
- Application Example: Photo OCR
6.Business Problems Can Be Solved Using Machine Learning:
- Understanding How Machine Learning Can Help
- Focus On The Business Problem
- Bringing data silos together
- Avoiding troubles to occur
- Getting the focus of customers
- Machine Learning for Business
7.Ten Predictions On The Future Machine Learning
- Determining the skill that you need
- Getting educated
- IBM-Recommended Resources
- Applying Machine Learning To Patient Health
- Leveraging IoT to create more predictable outcomes
- Proactively Responding To IT Issues
- Protecting against fraud
- What is Machine Learning
- Proficient in optimizing and fine-tuning ML models.
- Knowledge of ethical considerations in ML applications.
- Strong foundation in the latest ML techniques and algorithms.
- Skills to implement ML solutions across diverse domains.
- Confidence in evaluating and validating model performance.
- Opportunity to contribute to groundbreaking ML advancements.
- Continuous professional growth and learning opportunities.
- In-depth understanding of machine learning principles.
- Ability to develop advanced predictive models.
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