In business applications where the information in the data is spread over many features, problems arise: either very poor model performance or too little computing power. In this course, we teach you methods to build a model with good model validation scores and fast performance. This course will prepare you to tackle any situation through strategic methods for reducing data dimensionality, validation metrics for outcomes, and business applications of many feature situations. With the aid of our expert trainers, you will apply these skills to real and common cases to realize business opportunities with your own applications.
Why is this for you?
Have you ever been stumped by the sheer volume of information and been left not knowing where to start? Or discovered that the number of variables has made it impossible to perform a good explorative analysis before you even start modeling? This module has been designed to show you the different techniques to solve these issues and ensure you can handle even the largest data sets imaginable.
Who should attend?
This is an advanced level training for Data Scientists who have completed badge Advanced Model Optimization (3330). It involves tough coding challenges and various abstract topics which means you need to be advanced in Python and modeling principles.
What will you learn?
- The problems of many feature situations and typical cases when they arise
- Methods for reducing data dimensionality
- How to apply several techniques in a step-by-step approach
- An overview and calculation of validation metrics
- How to interpret outcomes of reduction methods
- Business outcomes
- Understanding problems with many feature situations – Being able to explain what issues there are when working with many features
- Methods for reducing data dimensionality – Proficient in choosing the right method for dimensionality reduction and explaining this
- Applying data dimensionality reduction techniques – Proficient in applying dimensionality reduction methods to large data sets
- Validation of dimensionality reduction methods – Knowing how to score and validate outcomes of your dimensionality reduction
- Business applications of many feature situations – Spotting business opportunities for many feature situations
Theory and practical use
All trainings in the GAIn portfolio combine high-quality standardized training material with theory sessions from experts and hands-on experience where you directly apply the material to real-life cases. Each training is developed by top of the field practitioners which means they are full of industry examples along with practical challenges and know-how, fueling the interactive discussions during training. We believe this multi-level approach creates the ideal learning environment for participants to thrive.
- Machine Learning
Open Course Schedule
MIacademy does offer part of its portfolio in an Open Course Schedule Format in our location in the center of Amsterdam. Via the form below you can register your interest to participate. Our team will contact you to finalize the booking and answer any questions you may have.
All of our courses are delivered by our expert trainers.
If no dates are mentioned. The specific course is not scheduled yet in 2020. If this is the case you can use the form to register your interest. In case there is enough demand MIacademy can schedule additional courses and will notify you.
Are you are interested to train a larger group of people, looking for specific training pe or and/or interested in creating a company-wide program? We will be happy to assist!
Whether you have a very specific training need (for example: training your Data Engineers on advanced technical topics, or your Data Scientists on model implementation), or the need for a large transformational program, or something in between, we can help. Over the past 13 years, we have built up extensive experience not only in the implementation of multi-year, multi-population, multi-country programs but also in providing high quality, very specific modules for specific target groups. Both in in-house set-ups and cross-company programs. Not sure what type of program would fit your organization best? We’d be happy to discuss the best approach together.