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Machine Learning With Pandas and Sklearn

Event status: Canceled
This event will not appear on the public calendar until it has been approved. If this does not happen soon, contact [email protected] for assistance.

Setup Time:
15 minutes
Start:
Saturday, August 25, 2018 at 09:00am
End:
Sunday, August 26, 2018 at 05:00pm
Teardown Time:
15 minutes
Member:
Type:
Lecture
Estimated size:
25
Contact:
Sri P
URL:
Fee:
700
Rooms:
Large Event Room

Details:
Description
Machine Learning applies various techniques to make the machine “learn” from data. It does not require explicit programming of rules. In this course, students will learn the fundamentals of machine learning and will program machine learning using numpy, pandas, and sklearn. Students will build prediction models of different complexities. By the end of the class, students will have a working knowledge about machine learning environment and sample projects.

Topics Include:
1. Numpy, Pandas, and Sklearn
2. Linear and logistic regression
3. K-means and Naïve Bayes classifier
4. Decision tree and Random forest
5. Support Vector Machine (SVM)
6. Bagging and boosting

We strongly believe that practice is the way to perfection and hence there will be plenty of in-class activities so that attendees will get an opportunity to try the material taught in the class. The attendees will have multiple opportunities to ask questions.

At the conclusion of the course, you will be able to:
• Prepare data for machine learning using Pandas and numpy, the de-facto standard for data preparation in Python.
• Use the common machine learning architectures such as Linear and logistic regression, K-means and Naïve Bayes classifier, Decision tree and Random forest, Support Vector Machine (SVM), Bagging and boosting that are used in the industry.
• Discuss the significance of hyper-parameters in the architectures.
• Debug and understand the inner working of the machine learning architectures.

Pre-requisites
Moderate level of computer programming ability in Python.

Notes: