Examples

MODEL EVALUATION & OPTIMIZATIONWhen all models have similar accuracy, now what?12 min read·18 hours agoYou’ve trained several classification models, and so they all appear to be performing well with high accuracy scores. Congratulations!But hold...

Data ScienceExplore the facility of and save time in data evaluationData isn't clean and never within the required structure!!Whether you're starting with data science or are an experienced skilled — You won’t deny...

Supercharge Your FastAPI with Middleware: Practical Use Cases and ExamplesMiddleware sits between an API router its routes, acting as a layer where you'll be able to run code before and after a request is...

ENSEMBLE LEARNINGFitting to errors one booster stage at a timeAfter all, in machine learning, we would like our predictions spot on. We began with easy decision trees — they worked okay. Then got here...

ENSEMBLE LEARNINGPutting the burden where weak learners need it mostEveryone makes mistakes — even the only decision trees in machine learning. As a substitute of ignoring them, AdaBoost (Adaptive Boosting) algorithm does something different:...

CLASSIFICATION ALGORITHMBell-shaped assumptions for higher predictions⛳️ More CLASSIFICATION ALGORITHM, explained: · Dummy Classifier · K Nearest Neighbor Classifier · Bernoulli Naive Bayes ▶ Gaussian Naive Bayes · Decision Tree Classifier · Logistic Regression ·...

An introduction to the mechanics of AutoDiff, exploring its mathematical principles, implementation strategies, and applications in currently most-used frameworksAt the center of machine learning lies the optimization of loss/objective functions. This optimization process heavily...

DATA PREPROCESSINGOne (tiny) dataset, six imputation methods?Let’s discuss something that each data scientist, analyst, or curious number-cruncher has to take care of in the end: missing values. Now, I do know what you’re considering...