Tag

tensorflow

From Machine Learning to Automated Machine Learning

From Automated Machine Learning in Action by Qingquan Song, Haifeng Jin, and Xia Hu

This article covers

•   Defining and introducing the fundamental concepts of machine learning

•   Describing the motivation for and high-level concepts of automated machine learning

Learn How to Model Language as Tensors

In case you missed it, here is Chris Mattmann and Dr. Scott Penberthy’s live Twitch coding stream recap. For more, check out the book: Machine Learning with TensorFlow, Second Edition. For more live coding streams, subscribe to Manning’s Twitch channel… Continue Reading →

Sentiment Classification Using a Large Movie Review Dataset, Part 2

From Machine Learning with TensorFlow, Second Edition by Chris Mattmann This article covers: Building sentiment classifier using logistic regression and with softmax Measuring classification accuracy Computing ROC curve and measure classifier effectiveness Submitting your results to the Kaggle challenge for… Continue Reading →

Sentiment Classification Using a Large Movie Review Dataset, Part 1

From Machine Learning with TensorFlow, Second Edition by Chris Mattmann

This article covers using text and word frequency (Bag of Words) to represent sentiment.

The Cool Way to Search Text

The Cool Way to Search Text

By Scott Penbertht and Chris Mattmann

Leverage the Power of Machine Learning

From Machine Learning with TensorFlow, Second Edition by Chris A. Mattmann

A New Approach to Deep Learning

From Probabilistic Deep Learning with Python by Oliver Dürr, Beate Sick, and Elvis Murina


slideshare-a-new-approach-to-deep-learning

Deep Learning with TensorFlow.js

From Deep Learning with JavaScript by Shanqing Cai, Stanley Bileschi, Eric D. Nielsen with Francois Chollet


slideshare-deep-learning-with-tensorflowjs

Recurrent Neural Networks

From Machine Learning with TensorFlow by Nishant Shukla

To bestow neural networks with contextual cues, we’ll study an architecture called a recurrent neural network. Instead of natural language data, we’ll be dealing with continuous timeseries data, like stock-market prices. By the end of the article, you’ll be able to model the patterns in timeseries data to make predictions about future values.

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