article thumbnail

Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

article thumbnail

AI In Analytics: Today and Tomorrow!

Smarten

Anomaly Alerts KPI monitoring and Auto Insights allows business users to quickly establish KPIs and target metrics and identify the Key Influencers and variables for the target KPI.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models. 7) Deep learning (DL) may not be “the one algorithm to dominate all others” after all.

article thumbnail

R vs Python: What’s the Best Language for Natural Language Processing?

Sisense

Using XG-Boost to model the text data resulted in an almost identical score for Python and R. There are many performance metrics to evaluate performance of Machine Learning models. This metric can be used in classification analyses to identify a model’s ability to predict a desired attribute, based on the training data.

article thumbnail

Five machine learning types to know

IBM Big Data Hub

Unsupervised machine learning Unsupervised learning algorithms—like Apriori, Gaussian Mixture Models (GMMs) and principal component analysis (PCA)—draw inferences from unlabeled datasets, facilitating exploratory data analysis and enabling pattern recognition and predictive modeling.

article thumbnail

Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning.

Modeling 139
article thumbnail

Better Forecasting with AI-Powered Time Series Modeling

DataRobot Blog

While AI-powered forecasting can help retailers implement sales and demand forecasting—this process is very complex, and even highly data-driven companies face key challenges: Scale: Thousands of item combinations make it difficult to manually build predictive models. A variety of models are been trained in parallel.