AI Tutorials

Discover Long Short-Term Memory (LSTM) networks in Python and how you can use them to make stock market predictions!

This Keras tutorial introduces you to deep learning in Python: learn to preprocess your data, model, evaluate and optimize neural networks.

In this tutorial to deep learning in R with RStudio's keras package, you'll learn how to build a Multi-Layer Perceptron (MLP).

Learn how to build a neural network and how to train, evaluate and optimize it with TensorFlow

Learn what Vision API is and what are all the things that it offers. By the end of this tutorial, you will also learn how you can call Vision API from your Python code.

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.