AI Tutorials

In this tutorial, you'll get an overview of Artificial Intelligence (AI) and take a closer look in what makes Machine Learning (ML) and Deep Learning different.

This tutorial covers stemming and lemmatization from a practical standpoint using the Python Natural Language ToolKit (NLTK) package.

Learn what cyclical learning rate policy is and how it can improve the training of a neural network.

There is an optimal number of hidden layers and neurons for an artificial neural network (ANN). This tutorial discusses a simple approach for determining the optimal numbers for layers and neurons for ANN's.

In this tutorial, you will build four models using Latent Dirichlet Allocation (LDA) and K-Means clustering machine learning algorithms.

Visualize the training parameters, metrics, hyperparameters or any statistics of your neural network with TensorBoard!

Learn what Generative Adversarial Networks are without going into the details of the math and code a simple GAN that can create digits!

Learn how to perform tidy sentiment analysis in R on Prince's songs, sentiment over time, song level sentiment, the impact of bigrams, and much more!

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.

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

Learn to scrape novels from the web and plot word frequency distributions; You will gain experience with Python packages requests, BeautifulSoup and nltk.