IBM Developer Newsletters

Analytics

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Analytics – July 2020

Using data and AI in your decision-making process.

Analytics – June 2020

Use data virtualization to make queries across multiple data sources, learn practical tips to create effective taxonomy, and automate model building with AutoAI.

Analytics – May 2020

Use statistical software to analyze COVID-19 data, create a climate rating system, build reactive applications with Kafka, and analyze sentiment and emotion of customer reviews.

Analytics – April 2020

Create a climate rating system, understand customer feedback, and learn to use Node-Red and pandas.

Analytics – March 2020

Forecast consumer demand using deep learning, build, train, and evaluate a machine learning product-based classifier, and encourage additional purchases based on past buying behavior.

Analytics – February 2020

Automate model building with AutoAI, use plots and charts in data visualization, and integrate AI into your IoT solutions.

Analytics – November 2019

Infuse your apps with AI, manage and monitor cell tower call drops, and predict fraud using AutoAI.

Analytics – October 2019

Get started with the Model Asset Exchange, deploy deep learning models, and predict home values using Golang and in-memory database machine learning functions.

Analytics – September 2019

Collecting home sales data using a high-performance CRUD app, validating computer vision deep learning models, and creating models easier and faster using open source connectors.

Analytics – August 2019

Gain customer insights from product reviews, create an Alexa skill with serverless and a conversation, and rapidly ingest and analyze streamed data.

Analytics – July 2019

Build an earthquake monitoring system, Visualize data with Python, and Validate computer vision deep learning models.

Analytics – June 2019

Analyze traffic data, create a health data analytics app, and extract live unstructured company data.

Analytics – May 2019

Analyze historical shopping data, determine what’s trending, and perform a machine learning exercise.

Analytics – April 2019

Scrape data from the web, display live insights, and improve your decision making.

Analytics – February 2019

Predict the stock market, infuse AI into your app, and quickly source and share your data sets.

Analytics – January 2019

Target better applicants, run predicates, and visualize your results.

Analytics – December 2018

Assign your wine, hunt for spam, and discover new customer trends.

Analytics – November 2018

Train a cloud-based machine learning model using on-premise data and create visualizations that enable responsible investing.

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