Monthly Archives: January 2023
Amazon AWS Certified Machine Learning Specialty – Modeling Part 13
34. Amazon Comprehend Up next, we’re going to go outside the world of Amazon, Sage Maker and into the higher level AI and ML services that AWS offers. These are services that aren’t really geared toward machine learning experts. They’re really more for anyone who just wants to use ML capabilities. So you don’t necessarily… Read More »
Amazon AWS Certified Machine Learning Specialty – Modeling Part 12
32. Automatic Model Tuning Let’s talk about automatic model tuning within Sage Maker, which is a very exciting capability of the Sage Maker system. So hyper parameter tuning is kind of a really big problem in the world of machine learning. So for all these algorithms we talked about, we’ve talked about the different hyper… Read More »
Amazon AWS Certified Machine Learning Specialty – Modeling Part 11
30. IP Insights in SageMaker And let’s cover the IP insights algorithm in Sage maker. IP Insights is all about finding fishy behavior in your web logs. So it’s an unsupervised technique that learns the usage patterns of specific IP addresses and it automatically identifies suspicious behavior from given IP addresses. So it can identify… Read More »
Amazon AWS Certified Machine Learning Specialty – Modeling Part 10
26. K-Nearest-Neighbors (KNN) in SageMaker Next up is KNN, which is probably the world’s simplest machine learning algorithm out there. K nearest neighbors, but Sage Maker does take it to the next level. If you’re not familiar with KNN and how it works, it’s really simple. Basically you plot your data points in some sort… Read More »
Amazon AWS Certified Machine Learning Specialty – Modeling Part 9
23. Random Cut Forest in SageMaker Next we’ll cover random cut forest, and that’s Amazon’s algorithm for anomaly detection. And it works in an unsupervised setting. So basically it’s looking at a series of data and trying to find things that are anomalous in that series. What things are sticking out is maybe being a… Read More »
Amazon AWS Certified Machine Learning Specialty – Modeling Part 8
20. Object Detection in SageMaker Up next is a fun one object Detection everyone loves computer vision and I’m no exception. So it does what it says it does. It detects objects in an image. And not only does it detect what objects are in the image, it will also give you bounding boxes that… Read More »
Amazon AWS Certified Machine Learning Specialty – Modeling Part 7
17. DeepAR in SageMaker Up next in our sage maker BC area is Deep AR. Deep AR is used for forecasting one dimensional time series data. So it’s kind of the classic use case of an RNN of a recurrent neural network. So we’re looking at a sequence of data points over time and trying… Read More »
Amazon AWS Certified Machine Learning Specialty – Modeling Part 6
14. Linear Learner in SageMaker Let’s start diving into the long list of builtin algorithms that Sage Maker offers. You will actually be expected to know about these things and the things that are special and quirky about each one. So pay attention, guys. Take notes. It’s all important. We’ll start with linear learner, which… Read More »
Amazon AWS Certified Machine Learning Specialty – Modeling Part 5
11. Precision, Recall, F1, AUC, and more Let’s talk about some metrics that you can derive from a confusion matrix. The stuff is super important on the exam, guys, so pay attention. So let’s revisit our friend, the confusion matrix. Again, in this particular example of one, we have actual values going down the columns… Read More »
Amazon AWS Certified Machine Learning Specialty – Modeling Part 4
8. Grief with Gradients: The Vanishing Gradient problem Something that kind of surprised me on the exam was how much depth they expect you to have on various edge cases around training a neural network. A couple of them involve gradients and some numerical issues with them. So let’s dive into that. Maybe you haven’t… Read More »