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Chicago: Machine Learning Corporate Training
Equip your team with in-demand machine learning skills in this hands-on course covering regression models, decision trees, and random forests. Learn practical techniques for data cleaning, model evaluation, and avoiding common pitfalls, all taught with visual explanations and real-world applications.
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| Location | At your location, Chicago | |||||||||||||||
| Pricing |
$1,800 for up to 20 people
We're happy to discuss your training needs free of charge. Reach out for a free consultation and let us know which skill your team is interested in, your preferred custom training options, and the approximate number of participants you’ll have so we can create a package for you. Send us an email or give us a call today! |
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| Duration |
Up to 7 hours For a shortened session, please request desired length in special requests at checkout.
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| Group Size |
Up to 20 people Group size can be changed after booking if needed.
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| Materials | None required | |||||||||||||||
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General Notes
Supported Platforms for Virtual Events: Zoom is our recommended platform, but we can accommodate Google Meets, Microsoft Teams, and WebEx if you provide the meeting link to CourseHorse in advance of the event. PoliciesPrice Match GuaranteeIf you find a similar event with a competitor at a lower price, we’ll gladly match it. This applies to events of comparable description and duration. Simply provide the details when booking, or within 72 hours of your booking, and we’ll ensure you get the best value. Contact an event concierge to get started. Rescheduling & Cancellation PolicyReschedule or cancel your event by emailing us at [email protected].
Rescheduled events must occur within 1 year of the original event. |
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Description
Build and evaluate machine learning models using linear and logistic regression, k-nearest neighbors, decision trees and random forests. Explore the statistics behind model quality and overfitting through visual explanations and applied projects.
Prerequisite:
Comfort with Python, NumPy and Pandas is required. Beginners should complete the Python for Data Science Bootcamp first.
What You'll Learn at a Glance:
- Cleaning, balancing, and preparing real-world datasets using Pandas
- Implementing machine learning algorithms, including logistic regression, decision trees, and random forest, using the scikit-learn library
- Selecting effective input features to improve model performance
- Properly splitting data into training, test, and cross-validation sets to ensure reliable evaluation
- Key theoretical concepts: overfitting, the bias-variance trade-off, and regularization
- Evaluating model accuracy using appropriate metrics and choosing the right algorithm for each problem
Build a portfolio of projects demonstrating your model-building skills.
Custom solutions for every team:
Purchase Vouchers or Group Classes
Invest in your workforce by purchasing group vouchers, allowing employees to attend any course at their convenience on weeknights, weekdays, or weekends. Our classes are available live online and in person at our Manhattan offices. Larger voucher blocks come with a custom registration tracking portal so you can easily monitor enrollment.
With a broad range of courses on our calendar, there is no need to coordinate a single time that works for everyone. Employees can redeem their vouchers for whichever class fits their skill level, schedule, and preferred format.
Learn Relevant Skills from Industry Experts
Participants leave our sessions as confident, capable users ready to apply what they learned the very next day. They also keep their course files permanently, giving them a handy reference guide long after training ends.
Our project-driven curriculum and hands-on instruction accommodate every learning style. We replicate the real challenges employees encounter on the job, so training translates directly to results.
We have deep experience designing programs for onsite office sessions, sessions held at our Midtown Manhattan offices, and fully remote virtual formats. Every program can be tailored to your organization's specific needs.