1. Team 2: Graham Leech, Austin Woods, Cory Smith, Brent Niemerski

2. Agenda What it Means for Us Future of Machine Learning
What is Machine Learning
Machine Learning Models
Future of Machine Learning
What it Means for Us

3. What is Machine Learning
Human Brain Like
Generic algorithm with no theoretical limitations on what it can do. Similar to how the brain functions.
Continuous Learning
The platform continues to learn as more data is input.
Autonomous Capabilities
Brings together statistics and computer science to enable computers to carry out a given task without being programmed.

4. Modern Machine Learning Applications
Autonomous Vehicles
Search Engine Optimization
Image Curation
Social Media

5. Machine Learning Models
Decision Tree 01
Bayesian Network 04
Linear Regression 02
Support Vector Machine 05
Neural Network 03
Nearest Neighbor 06

6. IBM Watson - Linear Regression

7. The Future of Machine Learning
Algorithm retraining
Current vs future state
Constant data access
Cognitive Services
Detection, recognition, understanding
Adoption of Quantum Computing
Increased capacity
Data analytics
Algorithm Retraining: Currently, most machine learning systems train only once. Based on that initial training, the system will then address any new data or problems. Over time, the training information often becomes dated or imperfect. In the near future, more machine learning systems will connect to the internet and continuously retrain on the most relevant information.
Cognitive Services: With such services, developers can empower their applications to carry out various duties, such as vision recognition, speech detection, and speech understanding.
As this technology is continuing to evolve, we are likely to witness the development of highly intelligent applications that can increasingly speak, hear, see, and even reason with their surroundings.
Quantum Computing: could lead to faster processing of data, which could accelerate the ability to synthesize information and draw insights
Quantum-powered systems will provide a much faster and more heavy-duty computation to both supervised and unsupervised algorithms.
Then there is the help that quantum computing can deliver to data analytics. Here, quantum computers can undertake very complex calculations and simplify them down as well as tack huge data problems easily. This can be applied to all types of industries, including airlines, retail, manufacturing and many more. For example, NASA has incredible amounts of data that can be analyzed through quantum computing to deliver effective and safer space travel.

8. Class Relevance Decision Making Future Business Future Business
Business transformation
Job opportunities
Decision Making
Big Data
Powering decisions
Future Business
Business transformation
Understanding of technology fosters ability for implementation in company