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A complete environment for data science as a service.
IBM Watson Machine Learning Accelerator is a software solution that bundles IBM PowerAI, IBM Spectrum Conductor, IBM Spectrum Conductor Deep Learning Impact, and support from IBM for the whole stack including the open source deep learning frameworks. It provides an end-to-end, deep learning platform for data scientists. This series gives you an introduction to PowerAI and walks you through tasks such as classifying images and training Keras and MLlib models within a Watson Machine Learning Accelerator custom notebook. You could also accelerate machine learning using Snap ML and Watson Machine Learning Accelerator.
Jul 15, 2019
Artificial intelligenceData science+
LIVE on Sep 11 – Introduction to Machine Learning Algorithms
Setting up an artificial intelligence (AI) environment on IBM PowerVM virtualized IBM Power Systems
Machine learning & deep learning with IBM Watson Machine Learning Accelerator
Train XGboost models within Watson Machine Learning Accelerator
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Sep 10, 2019
Artificial intelligenceIBM AIX+
The focus of this tutorial is to provide a way to perform inferencing on data on AIX LPAR using a Linux LPAR inside a IBM Power systems server. This benefits in leveraging secure, high-speed and low overhead data movement between AI and Enterprise processing environment
Aug 30, 2019
Webcast - Introduction to Machine Learning Algorithms
Jul 22, 2019
Artificial intelligenceDeep learning+
Drive online advertising click-through prediction with Watson Machine Learning Accelerator, SnapML, and AC922.
Artificial intelligenceMachine learning+
Expedite credit default risk prediction with Watson Machine Learning Accelerator and AC922.
Learn how to train XGBoost models using Watson Machine Learning Accelerator. Download the Anaconda installer and import it into Watson Machine Learning Accelerator as well as creating a Spark instance group with a Jupyter Notebook that uses the Anaconda environment.
May 08, 2019
Apache SparkArtificial intelligence+
Customize a notebook package to include Anaconda, Watson PowerAI, and sparkmagic and use that to run a Keras model connect to a Hadoop cluster and execute a Spark MLlib model.
May 01, 2019
Use the Watson Machine Learning Accelerator Elastic Distributed Training feature to distribute model training across multiple GPUs and compute nodes.
Apr 26, 2019
Artificial intelligenceWatson Machine Learning Accelerator
Use the Snap Machine Learning library to accelerate the training of logistic regression and random forest models and employ the trained models to analyze credit risk.
Apr 08, 2019
Get an overview of the Snap ML library, which provides high-speed training of popular machine learning models, and look at several use cases for using it.
Apr 01, 2019
Take a look at the testing of generalized linear models (GLMs) from the Snap ML library on three different use cases that are related to the financial services sector.
Oct 16, 2018
Artificial intelligenceIBM PowerAI+
An end-to-end tour using a computer vision classification example with Watson Machine Learning Accelerator.
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