AI
Unlock the power of AI with IBM Watson.
| Name | Brand | Solution | Description |
| Data Science in Action : scoring your client with Watson Machine Learning | Power | AI | Data science is the study of data, like biological sciences are the study of biology; physical sciences, it's the study of physical reactions. It is combination of skills, science and solutions to translate data into a business story and business solution. With This demo, you will discover how to apply data science to score client and accept/reject credit or insurance. We will use IBM Watson Machine Learning. |
| Getting started with H20 on IBM Power Systems | Power | AI | IBM and H2O.ai have a shared vision of improving the reach and adoption of AI by bringing it to more software application developers, whether they have data science skills or not. H2O's machine learning (ML) software, Driverless AI, automates several key steps in the machine learning pipeline and Data Science process. This “data scientist in a box” solution, accelerated on Power9 and GPU, provides competitive advantage. please come and play with H20 DAI solution |
| Getting started as a Data Scientist | Power | AI | Data scientists are a new breed of analytical data experts, big data wranglers, who have the technical skills to solve complex problems, and the curiosity to explore what problems need to be solved. But what if you are a data analyst, DBA, architect, business person, etc.? This demo will cover aspects of machine learning for the non-data scientist with educative example of insurance client scoring: predicting accident |
| Getting started with PowerAI Vision (Visual Insights) | Power | AI | IBM PowerAI Vision is a video/image analysis platform. Join us to learn how to use the built-in deep learning models that learn to analyze images and video streams for classification and object detection. No prior knowledge in machine learning or coding is required. |
| Come and detect your first ATM bank fraud using SPSS on IBM Power Systems | Power | AI | Each Saturday evening, you go to withdraw 100 euros at your preferred ATM close to your preferred shop center. Someone stole your credit card, guessed your PIN code but didn't succeed in getting 5000 euros from your bank account. Why? Because of Machine Learning ! Based on this real case scenario (demo hosted in IBM Client Center), the goal of this lab is to show you how it is easy to implement Machine Learning Algorithm with SPSS to detect a fraud on ATM withdrawals. Participants first learn from a SPSS tool, then explore the different SPSS capabilities, and finally create a Machine Learning fraud model on existing ATM historical data. |
| Getting Started with Watson Studio | Power | AI | IBM Watson Studio is an environment that has everything a data scientist needs to be successful. The Experience is an interactive environment where data scientists can use multiple tools to activate their insights. Walk through a demo to experience these unique tools |
| Watson Machine Learning in Action : build your first chatbot | Power | AI | Chat Bots can recognize a customer’s intention and manage your client. Virtual agents (based on chat bots) go a step further: they understand what a person is trying to achieve with the interaction and can carry on a conversation. Both are based on Machine Learning solutions and during this lab, you will build from scratch, your first chat bot using Watson Machine Learning Solution |
| From Data to AI: hands on the Analytics Clients journey | Power | AI | Artificial Intelligence, Machine Learning and Analytics are trending buzzwords of our time. You probably read about them every day in different media and sometimes in different definitions, but as a regular customer you are wondering where are the actual implementations? This lab will demystify what AI, big data, machine learning is. You will experiment what really is descriptive, predictive, prescriptive and cognitive solutions, building an entire marketing use case (optimizing marketing campaign). First you will implement Marketing dashboard with Cognos, then build a predictive model with Jupyter Notebook and finally outperform your marketing ROI using IBM ILOG decision optimization |
| Python for beginners | Power | AI | |
| Python for Machine Learning | Power | AI | |