Episode 3: Machine Learning

Episode 3 : Data science and Machine Learning

In this episode, we juxtapose the different types of Machine Learning: supervised, unsupervised, semi-supervised, and reinforcement.

What is the difference between data science and machine learning?

• Machine learning is a sub-discipline within data science
• Machine learning is an application of artificial intelligence
• Machine learning is predictive analytics
• Prescriptive analytics and recommending a path forward

The different types of machine learning: supervised, unsupervised, semi-supervised, and reinforcement learning

Supervised machine learning: data is labeled and we know the outcome, using a predictive model and comparing your predicted results to the labeled outcomes.

• Classic examples of churn and spam vs non-spam
• Classification vs regression problems and how they differ

Unsupervised machine learning: data is not labeled and we don’t know the outcome.

• Clustering using a distance metric is involved, and we can get the attributes of different clusters
• Latent dich allocation (LDA) for topic modeling (categories not defined beforehand)

Semi-supervised machine learning

• Turning an unsupervised program into a supervised learning problem
• How do we determine accuracy and precision of semi-supervised machine learning?

Reinforcement learning

• Self-driving cars examples
• A car will make mistakes, a penalty system will prevent those mistakes from re-emerging in the future
• The AI agent continuously learns based on a set of penalties that are imposed
• There will be a growth in reinforcement learning in the future

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👥ABOUT US:

Laura and Vijay are data scientists who enjoy talking about data and  sharing their experiences, which is why they started this podcast. Laura  worked in credit risk modeling and experimental design. She is also an  amateur silversmith. Vijay worked on Deep Learning NLP models and  recommender systems. He also loves learning new things, like French. On  Deep Data Dive, they will share their work experiences, discuss data  science fundamentals, and chat with guests, and more.

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🎥VIDEO PRODUCTION & DESIGN:

• Dana Donovick, Passion Possible, LLC.
• [e-mail] • 206-222-0740