Some which we just try to belong to but know nothing of.
Random Research
Artificial Intelligence (AI) are Human-like capabilities such as understanding natural language, speech, vision, and making inferences from knowledge that will extend software beyond the apps. Explains how it can be used to build smart apps that help organizations be more efficient and enrich people’s lives
create your own visualizations based on real data
Build, evaluate, and optimize machine learning models; including classification, regression, clustering, and recommendation.
intuitive approach to building complex models that help machines solve real-world problems with human-like intelligence
Okay I digress.
So this all came about because....
I was honored to be invited as a reviewer for the projects in Innovation Challenge 2018 and it dawned on me how there are simple answers. and. we actually do not need to think too far to try and make an impact. We just need to see the existing problems and serve with our heart to want to make the world a better place.
The best ideas does not need to be BIG But instead those that make an impact in someone's life. So to share (hopefully) it was not meant to be a secret what I felt was the best idea.
Problem: Elderly inability to reach for items on the shelves.
Solutions: To install a lever so the shelves can rotate - the elderly can do some physio exercise while spinning the lever and at the same time do things independently themselves.
AWESOME idea right?
Side note: I chanced upon this course outline that I found quite interesting
Shall go and research about it. $530 for this course. Also not very expensive but I better make sure I have some interest before registering
Overview of Artificial Intelligence (AI) involving Machine Learning Tools and Techniques
- Predictive Analytics
- Modeling Techniques: Decision tree algorithms, Regression and Neural Networks
- Case Studies: Predictive analytics and applications on the human resource sector
Applications of Regression Modeling: Making sense of advanced regression models
- Multiple Linear Regression
- Binary Logistic Regression
- Applications of regression in payroll and claims analytics
- Applications of regression in compensation and benefit analysis
Advanced Artificial Machine Learning Algorithms and Models
- Predictive analytics - Neural Network: Case Studies and its applications
- Pattern discovery – Segmentation and Cluster analysis
- Association Rule Mining - Sequence Detection modeling: Case Studies and its applications
Model Evaluation
- Misclassification and Accuracy measures
- Average squared errors
Model Deployment and Model Management
- Best Practices and applications
Case Studies and Applications
- Increasing Employee Engagement using Text analytics
- Organizational risk management in attrition analysis: Identifying potential employees who are at risk of leaving the organization
- Visualizing data and information for better Staff Management and risk profiling
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