TDS Archive

The fascinating world of Voronoi diagrams

A brief introduction about this ubiquitous pattern and its applications

Deep Learning Course notebooks worth $2,000 are now open source

These notebooks form the basis of fast.ai founder Jeremy Howard’s new book and are used for a $2,000 worth Deep Learning course.

A Quick and Dirty Guide to Random Forest Regression

A hands on approach on Random Forest Regression

Multiple Time Series Classification by Using Continuous Wavelet Transformation

The purpose of this post is to show why the continuous wavelet transformation is so powerful and how to use it to classify multiple…

How-To: 4 Essential Parts of Multiprocessing in Python

Effective Python

AutoML for time series: definitely a good idea

Approaches for time series forecasting using AutoML and example of the forecast, which such models can produce

The Data ROI Pyramid: A Method for Measuring & Maximizing Your Data Team

Struggling to articulate the value of your data team? Learn how to calculate your data team’s return with the Data ROI Pyramid.

AutoML for time series: advanced approaches with FEDOT framework

An example of using FEDOT and other AutoML libraries on real-world data with gaps and non-stationarity

Implementing an Autoencoder in TensorFlow 2.0

How to Find Seasonality Patterns in Time Series

Using Fourier Transform to detect seasonal components

How to Get A Job in Data Science/Machine Learning With No Previous Experience

Take charge of your job search

A Proof of the Central Limit Theorem

If you like chocolate, this proof will feel like the multi-layered magic of a Mars bar

Hyperparameters Tuning for Machine Learning Model Ensembles

a little research for a pretty optimization

My Experience Switching From Power BI to Looker (as a Senior Data Analyst)

What you need to know before you switch from Power BI to Looker.

🤷 Quantifying Uncertainty — A Data Scientist’s Intro To Information Theory — Part 2/5: Entropy

Gain intuition into Entropy and master its applications in Machine Learning and Data Analysis. Python code provided. 🐍

Agentic Mesh: Towards Enterprise-Grade Agents

Enterprise-grade capabilities will make or break the future of agent adoption. Without them, agents adoption will collapse.

How AutoML helps to create composite AI?

Main trends and challenges in AutoML, the ideas behind implementations of composite AI, and the open-source framework FEDOT.

Proximal Policy Optimization (PPO) Explained

The journey from REINFORCE to the go-to algorithm in continuous control

Exploring Feature Extraction with CNNs

Using a Convolutional Neural Network to check specialization in feature extraction

😲 Quantifying Surprise — A Data Scientist’s Intro To Information Theory — Part 1/5: Foundations

Gain intuition into Information Theory and master its applications in Machine Learning and Data Analysis. Python code provided. 🐍

What to Do If a Time Series Is Growing (But Not in Length)

Just use AutoML for multivariate time series forecasting

Will 2025 Be the Year Real-Time Analytics Finally Goes Mainstream?

A deep dive into how (and why) streaming is becoming more accessible in the data space.

DIY AI: How to Build a Linear Regression Model from Scratch

How to implement a linear regression model in Python without using machine learning libraries

Variable Importance in Random Forests

Traditional Methods and New Developments

Organizing for AI

The interplay between ownership, outsourcing, and remote work