Most AI classes are either too brief to enable programmers to use machine learning (ML) and deep learning (DL) from raw data to useful decision—and when to use which technique—or are too long to devote the required weeks/months for sufficient understanding of how, and when, to use ML and DL in practice. We will leverage experience working with real customers to deliver an accelerated introduction to ML and DL covering all stages—from data preparation to training to inferencing—with real examples showcasing the power, and appropriate usage, of both. We will use pre-prepared scripts, data, and codes, and the ‘cooking show’ method of moving to completed versions of each step quickly, enabling listeners to understand each step without spending hours/days of actual data manipulation and coding.
Other Resources / Information
https://www.cio.com/article/3410558/enterprise-ai-a-look-at-three-fundamental-deep-learning-approaches.html and three previous articles in series (linked)
- Understand what AI and machine learning (ML) are, and learn the commonly used types both classical ML and deep learning (DL).
- 2. Learn how to choose the appropriate ML or DL techniques for different kinds of problems and purposes, and why.
- 3. Learn the entire process (steps) to get from raw data all the way to insight/prediction/decision with machine learning and deep learning.
- Jay Boisseau, AI & HPC Technology Strategist, Dell EMC
- Lucas Wilson, AI Researcher & Data Scientist, Dell EMC
Jay Boisseau, AI & HPC Technology Strategist, DELL Technologies
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