Complete tutorial on class balancing for anonymized knowledge for machine studying mannequin choice
I’m bringing you a Machine Studying Mannequin Choice undertaking for Multivariate Evaluation with Anonymized Knowledge.
This can be a complete undertaking the place we’ll go from begin to end — from defining the enterprise drawback to the mannequin deployment (although we’ll go away the deployment for an additional time).
There can be two full tutorials for this undertaking, and I wish to stroll you thru a variety of strategies, together with the added complexity of working with anonymized knowledge — one thing more and more frequent within the job market as a result of knowledge privateness considerations.
So, what’s the massive problem with engaged on this kind of knowledge? It’s that you simply don’t have any info on what every variable represents.
Now, that’s tough, isn’t it? You’ll obtain the info, and with out figuring out what every variable stands for, you’ll have to develop a machine studying mannequin from that.