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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.

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

2018年2月2日

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

2018年1月19日

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

2018年1月10日

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

2018年1月3日

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

2017年12月21日

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

2017年12月5日

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

2017年10月19日

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

2017年10月13日

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

2017年8月24日

Apache Spark Tutorial: ML with PySpark

Apache Spark tutorial introduces you to big data processing, analysis and ML with PySpark.

Karlijn Willems

2017年7月28日

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

2017年6月20日

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

2017年5月4日