Building and deploying machine learning pipelines in Python Course | in per...
Event Information
Description
Do you want to learn how to conduct effective data science for business? This hands-on, immersive course will teach you how to build and deploy a proper machine learning pipeline. Join Ziad, our expert in Internet of Things, as he teaches you how to deploy regression and classification systems. He will teach you the best practices for feature selection, hyperparameter tuning, model selection, and machine learning pipeline algorithms. By the end of the course, you will have built an effective unsupervised model for anomaly detection and will deploy the algorithm to production through a python web app.
Join us for this 4 days 5:30 to 9:00 evening workshop. Dinner and snacks will be provided. Windows or Apple laptop required.
Agenda:
- Day 1: Introduce Linear Reg and variable selection methods
- Day 2: Model selection and cross validation pipelines. Introduce Bias/Variance tradeoff
- Day 3: Classification with logistic regression, Random Forrest and XGBoost. Discuss loss functions and gradient descent
- Day 4: Introduce Customized Pipelines, and use them for variable selection, model selection and putting models in production with web app
Why this class:
- The business case: We provide a real data set represeting a real business problem. This class will use aircraft engine data. Learners will apply state of the art learning algorithms to analyse engine behavior and recommend maintenance activities.
- The Experts: The instructors are industry experts, they have built and deployed enterprise grade machine learning algorithms
- The setup: This is in person training, not through hangout or tape delayed. We have several experts in the class room that will help answer questions. Our infrastructure is setup through AWS. No need to spin up virtual machines
- The Curriculum: Carefully designed by our experts to help attendees learn machine learning and be able to use this knowledge on a project or during an interview
For any questions regarding this course, contact us:
Ziad Katrib
Email: ziad@foundation3.ai
