The Basics of Object Detection: YOLO, SSD, R-CNN

Overview of how object detection works, and where to get started

7 Techniques to Handle Imbalanced Data - KDnuggets

This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.

Chi-Square Test to Compare Categorical Variables

Complete Guideline to Find Dependencies among Categorical Variables with Chi-Square Test

The Mindset Technique to Understand Precision and Recall Like Never Before

Precision and Recall elaborated with sample situations

Pricing at Lyft

By Yanqiao Wang

Principal Component Analysis: Everything You Need To Know

Covariance, eigenvalues, variance and everything …

[P] My co-founder and I quit our engineering jobs at AWS to build “Tensor Search”. Here is why.

530 votes, 63 comments. My co-founder and I, a senior Amazon research scientist and AWS SDE respectively, launched Marqo a little over a week ago - a…

Linear Regression Analysis – Part 1 - DataScienceCentral.com

Who should read this blog: Someone who is new to linear regression. Someone who wants to understand the jargon around Linear Regression Code Repository: https://github.com/DhruvilKarani/Linear-Regression-Experiments Linear regression is generally the first step into anyone’s…

Introduction to Embedding, Clustering, and Similarity

Introduction to key elements of ML and Autoencoders: Embedding, Clustering, and Similarity.

An Intuitive Explanation of Collaborative Filtering

The post introduces one of the most popular recommendation algorithms, i.e., collaborative filtering. It focuses on building an intuitive understanding of the algorithm illustrated with the help of an example.

How to Use UMAP For Much Faster And Effective Outlier Detection

Let’s catch those high-dimensional outliers

Multi-Objective Ranking for Promoted Auction Items

Determining which promoted auction items to display in a merchandising placement is a multi-sided customer challenge that presents opportunities to both surface amazing auction inventory to buyers and help sellers boost visibility on their auction listings.

Adjacency networks

Finding the adjacency graphs for US states and Texas counties using Mathematica

https://www.einblick.ai/blog/problems-with-notebooks-msftpaper/

Demystifying Object Detection and Instance Segmentation for Data Scientists - MLWhiz

this post is explaining how permutation importance works and how we can code it using ELI5

Patterns, Predictions, and Actions

How to Perform Motion Detection Using Python - KDnuggets

In this article, we will specifically take a look at motion detection using a webcam of a laptop or computer and will create a code script to work on our computer and see its real-time example.

SHAP for Categorical Features with CatBoost

Avoid post-processing the SHAP values of categorical features

9 Visualizations with Python that Catch More Attention than a Bar Chart

Creating eye-catching graphs with Python to use instead of bar charts.

OCR-free document understanding with Donut

Use the recently-released Transformers model to generate JSON representations of your document data

An Introduction to Graph Partitioning Algorithms and Community Detection

Graph partitioning has been a long-lasting problem and has a wide range of applications. This post shares the methodology for graph…

5 Less-Known Python Libraries That Can Help in Your Next Data Science Proje

Reduce time in your data science workflow with these libraries.

https://twitter.com/freakonometrics/status/1550439602594484225?s=12&t=5dAyRh9A5Nw53A3oNf4HPg

Building classifiers with biased classes: AdaSampling comes to the rescue

An algorithmic approach to clean up your dataset and sharpen class assignments.

What is YOLOv7? A Complete Guide.

In this guide, we discuss what YOLOv7 is, how the model works, and the novel model architecture changes in YOLOv7.

YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for...

YOLOv7 surpasses all known object detectors in both speed and accuracy in the range from 5 FPS to 160 FPS and has the highest accuracy 56.8% AP among all known real-time object detectors with 30...

Modeling Marketing Mix Using Smoothing Splines

Capturing non-linear advertising saturation and diminishing returns without explicitly transforming media variables

Linear Algebra for Data Science - KDnuggets

In this article, we discuss the importance of linear algebra in data science and machine learning.

Build Complex Time Series Regression Pipelines with sktime

How to forecast with scikit-learn and XGBoost models with sktime

Machine Learning Operations (MLOps): Overview, Definition, and Architecture

The final goal of all industrial machine learning (ML) projects is to develop ML products and rapidly bring them into production. However, it is highly challenging to automate and operationalize...

Understanding Self-Organising Map Neural Network with Python Code

Brain-inspired unsupervised machine learning through competition, cooperation and adaptation

How to Solve Scheduling Problems in Python

Use linear programming to minimize the difference between required and scheduled resources

what is discriminant analysis at DuckDuckGo

Want to know what is discriminant analysis & how does it help in analyzing data? Read this complete guide on Discriminant analysis now.

Topological Data Analysis for Machine Learning

Probabilistic Numerics | Textbooks

Quantifying Uncertainty in Computation.

firmai/financial-machine-learning: A curated list of practical financial machine learning tools and applications.

A curated list of practical financial machine learning tools and applications. - firmai/financial-machine-learning

Essential Math for Data Science: Eigenvectors and Application to PCA - KDnuggets

In this article, you’ll learn about the eigendecomposition of a matrix.

An Introduction to Regularization

This is what makes your trained models actually usable

grahamjenson/list_of_recommender_systems: A List of Recommender Systems and Resources

A List of Recommender Systems and Resources.

Home Page of Evan Miller

Articles, software, calculators, and opinions.

T-LEAF: Taxonomy Learning and EvaluAtion Framework

How we applied qualitative learning, human labeling and machine learning to iteratively develop Airbnb’s Community Support Taxonomy.

FIGS: Attaining XGBoost-level performance with the interpretability and spe

The BAIR Blog

Three Performance Evaluation Metrics of Clustering When Ground Truth Labels

Which metric should be used to evaluate the clustering results if the ground truth labels are not available? In this post, I’m introducing…

Multi-Relevance Ranking Model for Similar Item Recommendation

Buyers reveal a whole range of behaviors and interests when they browse our pages, so we decided to incorporate these additional purchase intent signals into our machine learning model to improve the relevance of our recommended items.

Complete Step-by-step Genetic Algorithm from Scratch for Global Optimization

No need to worry about getting stuck in local minima anymore

The Battle of Choropleths — Part 3 — Folium

Using the Folium Package to Create Stunning Choropleths

Precision, Recall, and F1 Score of Multiclass Classification — Learn in Dep

Manual Calculation From a Confusion Matrix and the Syntax of sklearn Library

Super Study Guides

Illustrated study guides ideal for visual learners.

Neighborhood Analysis, KD-Trees, and Octrees for Meshes and Point Clouds in

How to use Python libraries like Open3D, PyVista, and Vedo for neighborhood analysis of point clouds and meshes through KD-Trees/Octrees

Time Series Forecasting with ARIMA

In this article, I will take you through the task of Time Series Forecasting with ARIMA using the Python programming language.