본문으로 바로가기
범주
Topics

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.
Other topics:
Group2명 이상을 교육하시나요?DataCamp for Business 사용해 보세요

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

2018년 2월 2일

Transfer Learning: Leverage Insights from Big Data

In this tutorial, you’ll see what transfer learning is, what some of its applications are and why it is critical skill as a data scientist.
Lars Hulstaert's photo

Lars Hulstaert

2018년 1월 19일

Machine Learning with Kaggle: Feature Engineering

Learn how feature engineering can help you to up your game when building machine learning models in Kaggle: create new columns, transform variables and more!
Hugo Bowne-Anderson's photo

Hugo Bowne-Anderson

2018년 1월 10일

Kaggle Tutorial: Your First Machine Learning Model

Learn how to build your first machine learning model, a decision tree classifier, with the Python scikit-learn package, submit it to Kaggle and see how it performs!
Hugo Bowne-Anderson's photo

Hugo Bowne-Anderson

2018년 1월 3일

Kaggle Tutorial: EDA & Machine Learning

In this Kaggle tutorial, you'll learn how to approach and build supervised learning models with the help of exploratory data analysis (EDA) on the Titanic data.
Hugo Bowne-Anderson's photo

Hugo Bowne-Anderson

2017년 12월 21일

Convolutional Neural Networks in Python with Keras

In this tutorial, you’ll learn how to implement Convolutional Neural Networks (CNNs) in Python with Keras, and how to overcome overfitting with dropout.
Aditya Sharma's photo

Aditya Sharma

2017년 12월 5일

LDA2vec: Word Embeddings in Topic Models

Learn more about LDA2vec, a model that learns dense word vectors jointly with Dirichlet-distributed latent document-level mixtures of topic vectors.
Lars Hulstaert's photo

Lars Hulstaert

2017년 10월 19일

Web Scraping & NLP in Python

Learn to scrape novels from the web and plot word frequency distributions; You will gain experience with Python packages requests, BeautifulSoup and nltk.
Hugo Bowne-Anderson's photo

Hugo Bowne-Anderson

2017년 10월 13일

Detecting Fake News with Scikit-Learn

This scikit-learn tutorial will walk you through building a fake news classifier with the help of Bayesian models.
Katharine Jarmul's photo

Katharine Jarmul

2017년 8월 24일

Apache Spark Tutorial: ML with PySpark

Apache Spark tutorial introduces you to big data processing, analysis and ML with PySpark.
Karlijn Willems's photo

Karlijn Willems

2017년 7월 28일

Scikit-Learn Tutorial: Baseball Analytics Pt 2

A Scikit-Learn tutorial to using logistic regression and random forest models to predict which baseball players will be voted into the Hall of Fame
Daniel Poston's photo

Daniel Poston

2017년 6월 20일

Scikit-Learn Tutorial: Baseball Analytics Pt 1

A scikit-learn tutorial to predicting MLB wins per season by modeling data to KMeans clustering model and linear regression models.
Daniel Poston's photo

Daniel Poston

2017년 5월 4일