Learning to add with LSTM

Using long-short term layers to learn to add.

Classic spam classification using Spark MLLib

Using MLLib naive Bayes for spam classification.

Spark GraphFrames basics

GraphFrames on Spark for the clueless.

Scraping the web using Mathematica

Scraping blogs, Pinterest and Facebook with Mathematica.

Fairness

It is a common misconception that AI is absolutely objective, since AI is objective only in the sense of learning what human teaches.

Text classification with Tensorflow 2.0

The classic IMDB classification based on Tensoflow 2.0

Fashion MNIST using Temsorflow 2.0

The MNIST fashion set consists of images of clothing, like sneakers and shirts. It's somewhat more complex than the the classic MNIST dataset.

Serving TensorFlow models

Restify TF networks and other ways to serve intelligence.

The Keras Functional API

The Keras API makes creating deep learning models fast and easy.

GPT2 using Mathematica and MXNet

A large-scale unsupervised language model which generates coherent paragraphs of text, achieves state-of-the-art performance on many language modeling benchmarks, and performs rudimentary reading comprehension, machine translation, question answering, and summarization—all without task-specific training.