MLOps Lifecycle with MLFlow, Airflow, Amazon S3, PostgreSQL
Full Machine Learning Lifecycle using Airflow, MLflow, and AWS S3.
Full Machine Learning Lifecycle using Airflow, MLflow, and AWS S3.
Investigate if ensemble feature selection methods are superior of individual in machine learning classification problems.
Feature engineering, selection, visualization, model development, feature explainability.
Learn basic theory about the 3 types of feature selection in machine learning namely filters, wrappers, and embedders.
Achieve ×66 speedup read time, ×25 write time, and ×0.39 filesize on your daily I/O operations.
Using the best Software Engineering practices to create a simple and modern app.
Merge IMDb with Wikipedia movie data and build, evaluate and visualize topics using LDA.
An app where anyone can join with Spotify credentials and see a lot of cool statistics about his/her profile.
Five Algorithms to rule them all, Five Algorithms to find them, Five Algorithms to bring them all and in the darkness bind them.
6 Classical Forecasting Methods are Compared with 3 Machine Learning Algorithms using code in Python on sales data from kaggle.
Stationarity. ADF stationarity Test. Autocorrelation, Lag Scatter plot. Moving Average, Double and Triple Exponential Smoothing.
What is a time series and which are the steps in a forecasting task? How to plot trends and seasonality? How to decompose?
For those of you that want to dive into the world of time series, this is the perfect place to start! Including visualizations for each important time series...
Clustering is the most common form of unsupervised learning. It is the process that involves the grouping of data points into classes of similar objects.
Given a single feature that contains date and time, I created a function that generates 23 features.
Code examples for histogram, kde, box, count, pie, scatter, join, reg, hex, line bar, violin, boxen, strip, correlation plots.
Let’s suppose that you want to relocate. You don’t know where, yet. You have enough money in order to relocate and then search for a job in your new city. Yo...
A very popular Kaggle kernel (110.000+ views, 1400+ upvotes, 200+ comments) that won me the 1st prize, as the most informative and upvoted kernel for the pop...
Why to use normalization and standardization? Which are their differences? When to use them and when to avoid?
Are you starting with Data Science? Pandas is the first thing you will need. Learn how to create, add, remove, rename, read, select, filter, sort, group, man...
Why to encode categorical features? 6 ways to encode different kinds of data.
The objective of this project is the Emotion Analysis of sentences that are comming from movie reviews, using Machine Learning. An attempt will be made to co...