Model deployment for real-time predictions is now available in Oracle Cloud Infrastructure Data ...
Oracle Data Science Blog
by Tzvi Keisar
3y ago
On March 19, 2021, Oracle Cloud Infrastructure (OCI) Data Science released a new feature called Model Deployment to enable the serving of machine learning models as HTTP endpoints and provide real-time scoring of data. This feature is available in the OCI Software Development Kits (SDKs), OCI Command Line Interface (CLI), and OCI Console. Machine learning, as complex as it may be, serves a business purpose, and that is using existing data to make predictions on future data. To meet that purpose, models that were trained on existing data need to be available to make predictions on fresh data th ..read more
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6 tips for easier AI adoption
Oracle Data Science Blog
by Kristen Lee
3y ago
It’s no surprise that companies across industries are turning to AI and machine learning. The worldwide AI market is forecast to reach $327.5 billion in 2021 and exceed $500 billion by 2024, according to IDC.  And yet, while many businesses know the importance of using AI to stay competitive, AI adoption isn’t always easy – it’s a comprehensive process, from data ingestion to model monitoring, and each step poses its own challenges. In Oracle Developer Live: AI and ML for Your Enterprise, Oracle experts shared their insights on how to use AI and machine learning for any business. Her ..read more
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New OCI Data Catalog release introduces AI and ML-based features for better productivity
Oracle Data Science Blog
by Guest Author
3y ago
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Graph machine learning with PyPGX and OML4Py
Oracle Data Science Blog
by Rhicheek Patra
3y ago
PyPGX and OML4Py enable users to develop fast, scalable, and secure graph machine learning applications. In this post, I'll show you how to build an intrusion detection system using PyPGX and OML4Py for graph machine learning.    What are PyPGX and OML4Py?  PyPGX is the newly released Python client for PGX, a toolkit for graph analysis developed by Oracle (available as the Property Graph feature of Oracle Database). OML4Py is the Python interface to Oracle Machine Learning (OML), which is a set of products that support scalable machine learning algorithms for ..read more
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Businesses trust robots more than humans to manage money
Oracle Data Science Blog
by Emma Hitzke
3y ago
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Build and deploy a machine learning model in 9 minutes using ONNX
Oracle Data Science Blog
by Allen Hosler
3y ago
Reading time: 9 mins What you’ll accomplish in this post: Build a machine learning model using AutoML Convert your model to ONNX format Save your model to the model catalog Deploy your model as a serverless function If you’ve ever tried to take a machine learning model to production, you know just how difficult it can be. While there’s been immense progress in training and evaluating models, the growth in open source resources for deploying models remains comparatively stagnant. This post covers an easy, secure, scalable workflow for machine learnin ..read more
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Optimizing estimators with the ADSTuner: A hyperparameter optimization engine
Oracle Data Science Blog
by Guest Author
3y ago
By Nupur Chatterji, Machine Learning Engineer, and John Peach, Principal Data Scientist A key step in model development is the optimization of hyperparameters. The ADSTuner class performs a hyperparameter search, sometimes called hyperparameter tuning. It does this by searching over a range or distribution of values looking for the best model. This powerful module is available as part of the most recent release of the Oracle Accelerated Data Science (ADS) library. This blog post shows you how to: Tune a model using the ADSTuner. Obtain tuning information. Customize the search space. Gene ..read more
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Accelerate machine learning in Oracle Cloud Infrastructure on NVIDIA GPUs with RAPIDS
Oracle Data Science Blog
by JR Gauthier
3y ago
Earlier this month, Oracle Cloud Infrastructure (OCI) Data Science released Conda Environments for notebook sessions. One of the environments available for (NVIDIA) GPU virtual machines (VMs)  is the RAPIDS (version 0.16) environment. In this post, I give an overview of NVIDIA RAPIDS and why it's awesome!  First, RAPIDS is a suite of open source machine learning libraries that lets machine learning engineers execute end-to-end machine learning and analytics pipelines entirely on GPUs. I like to think of RAPIDS as the "pandas+sklearn for GPUs", a flexible ..read more
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New Conda environment feature available in Oracle Cloud Infrastructure Data Science
Oracle Data Science Blog
by JR Gauthier
3y ago
On January 13, 2021, the Oracle Cloud Infrastructure (OCI) Data Science service released a new feature called Conda environments to the notebook session resource. This new feature includes a JupyterLab extension called the Environment Explorer, available through the JupyterLab Launcher tab, and a CLI tool called odsc conda available through the JupyterLab terminal window. These tools give you the capabilities to manage the lifecycle of Conda environments in notebook sessions. This is a major change to the notebook session resource that data scientists have been using since the OCI Data S ..read more
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A simple guide to building a confusion matrix
Oracle Data Science Blog
by Guest Author
3y ago
By Shabbir Tayabali, Consulting Technical Manager In this post, I'll discuss how a confusion matrix benefits machine learning; I'll also share a case study.  Subscribe to the Oracle AI & Data Science Newsletter to get the latest AI, machine learning, and data science content sent straight to your inbox!  What is a confusion matrix? A confusion matrix is a way of assessing the performance of a classification model. It is a comparison between the ground truth (actual values) and the predicted values emitted by the model for the target variable. A confusion matrix is usefu ..read more
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