Byte
Regression is a technique in statistics and machine learning, in which the value of an independent variable is predicted by its relationship with other variables. Frameworks like Scikit-Learn and XGBoost make it easier than ever to perform regression with a wide variety of models - one of the recently well-adopted...
David Landup
Scikit-Learn's scalers are the backbone of practically all regressors and classifiers built on top of them, scaling the data to a workable range and preparing a latent representation to learn from. If you'd like to read more about feature scaling, read our "Feature Scaling Data with Scikit-Learn for Machine...
RandomizedSearchCV and GridSearchCV allow you to perform hyperparameter tuning with Scikit-Learn, where the former searches randomly through some configurations (dictated by n_iter) while the latter searches through all of them. XGBoost is an increasingly dominant library, whose regressors and classifiers are doing wonders over more traditional implementations, and is...
Saving and loading Scikit-Learn models is part of the lifecycle of most models - typically, you'll train them in one runtime and serve them in another. In this Byte - you'll learn how to save and load a regressor using Scikit-Learn. First off, let's build a simple regressor and fit...
So - you've trained a sparkling regressor using XGBoost! Which features are the most important in the regression calculation? The first step in unboxing the black-box system that a machine learning model can be is to inspect the features and their importance in the regression. Let's quickly train a mock...
Article
If you had studied longer, would your overall scores get any better? One way of answering this question is by having data on how long you studied for and what scores you got. We can then try to see if there is a pattern in that data, and if in...
Cássia Sampaio
Scikit-Learn is one of the most widely-used Machine Learning library in Python. It's optimized and efficient - and its high-level API is simple and easy to use. Scikit-Learn has a plethora of convenience tools and methods that make preprocessing, evaluating and other painstaking processes as easy as calling a single...
This guide is an in-depth introduction to an unsupervised dimensionality reduction technique called Random Projections. A Random Projection can be used to reduce the complexity and size of data, making the data easier to process and visualize. It is also a preprocessing technique for input preparation to a classifier or...
Mehreen Saeed
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