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Machine Learning Tutorial
Get insights & best practices into AI & machine learning, upskill, and build data cultures. Learn how to get the most out of machine learning models with our tutorials.
Random Forest Classification with Scikit-Learn
This article covers how and when to use Random Forest classification with scikit-learn. Focusing on concepts, workflow, and examples. We also cover how to use the confusion matrix and feature importances.
Adam Shafi
February 24, 2023
Demystifying Generative Adversarial Nets (GANs)
Learn what Generative Adversarial Networks are without going into the details of the math and code a simple GAN that can create digits!
DataCamp Team
May 9, 2018
Absolute and Weighted Frequency of Words in Text
In this tutorial, you'll learn about absolute and weighted word frequency in text mining and how to calculate it with defaultdict and pandas DataFrames.
Elias Dabbas
April 24, 2018
A Beginner's Guide to Object Detection
Explore the key concepts in object detection and learn how they are implemented in SSD and Faster RCNN, which are available in the Tensorflow Detection API.
Lars Hulstaert
April 19, 2018
K-Means Clustering in R Tutorial
Learn what k-means is and discover why it’s one of the most used clustering algorithms in data science
Eugenia Anello
March 21, 2023
From Local Machine to Dask Cluster with Terraform
Learn how you can take local code that does grid search with the Scikit-Learn package to a cluster of AWS (EC2) nodes with Terraform.
DataCamp Team
March 8, 2018
Feature Selection in R with the Boruta R Package
Tackle feature selection in R: explore the Boruta algorithm, a wrapper built around the Random Forest classification algorithm, and its implementation!
DataCamp Team
March 7, 2018
Experts' Favorite Data Science Techniques
What are the most favorite techniques of the professional data scientists interviewed in DataFramed, a DataCamp podcast? Explore all 6 of them in this tutorial!
Hugo Bowne-Anderson
February 28, 2018
Ensemble Learning in R with SuperLearner
Boost your machine learning results and discover ensembles in R with the SuperLearner package: learn about the Random Forest algorithm, bagging, and much more!
Daniel Gremmell
February 20, 2018
Active Learning: Curious AI Algorithms
Discover active learning, a case of semi-supervised machine learning: from its definition and its benefits, to applications and modern research into it.
DataCamp Team
February 9, 2018
Finding Similar Names with Matrix Factorization
Applying matrix factorization on user clicks on hundreds of names on the recommender system NamesILike.com reveal an unseen structure in our first names.
DataCamp Team
February 2, 2018
Lyric Analysis with NLP & Machine Learning with R
Dive into the lyrics of Prince's music with R: use text mining and Exploratory Data Analysis (EDA) to shed insight on The Artist's career.
Debbie Liske
February 2, 2018