Delivered for #aOSMumbai as a level 101 session on getting started with Azure Machine learning studio.
In this session we showed how to predict the price of a car.
Learn why continual learning is important, and how to use it in your machine learning models to improve accuracy. You can download the full webinar here: https://info.cnvrg.io/continual-learning-webinar
Learn why continual learning is important, and how to use it in your machine learning models to improve accuracy. You can download the full webinar here: https://info.cnvrg.io/continual-learning-webinar
This is a part of presentation done at Global Azure BootCamp 2017 Mohali Location.
We talked about how to get started with your first data science experiment using Azure Machine Learning Studio.
Integrating Azure Machine Learning and Predictive Analytics with SharePoint O...Bhakthi Liyanage
Windows Azure Machine Learning and Data Analytics platform offers a streamlined experience, from setting up with only a web browser to using drag-and-drop gestures and simple data-flow graphs to set up experiments. Azure Machine Learning Studio features a library of time-saving sample experiments, R and Python packages, and best-in-class algorithms from Microsoft businesses like Xbox and Bing. Learn how the Azure Machine Learning service in the cloud lets you easily build, deploy, and share advanced analytics solutions into your SharePoint platform. Attendees will also gain knowledge on special considerations that should be taken in to account when creating analytical models. The demo will walk you through creating an analytic model in Azure ML studio and consume the model within SharePoint online.
This presentation covers an overview of Analytics and Machine learning. It also covers the Microsoft's contribution in Machine learning space. Azure ML Studio, a SaaS based portal to create, experiment and share Machine Learning Solutions to the external world.
Microsoft DevOps for AI with GoDataDrivenGoDataDriven
Artificial Intelligence (AI) and machine learning (ML) technologies extend the capabilities of software applications that are now found throughout our daily life: digital assistants, facial recognition, photo captioning, banking services, and product recommendations. The difficult part about integrating AI or ML into an application is not the technology, or the math, or the science or the algorithms. The challenge is getting the model deployed into a production environment and keeping it operational and supportable. Software development teams know how to deliver business applications and cloud services. AI/ML teams know how to develop models that can transform a business. But when it comes to putting the two together to implement an application pipeline specific to AI/ML — to automate it and wrap it around good deployment practices — the process needs some effort to be successful.
Automated machine learning (automated ML) automates feature engineering, algorithm and hyperparameter selection to find the best model for your data. The mission: Enable automated building of machine learning with the goal of accelerating, democratizing and scaling AI.
This presentation covers some recent announcements of technologies related to Automated ML, and especially for Azure. The demonstrations focus on Python with Azure ML Service and Azure Databricks.
This presentation is the fourth of four related to ML.NET and Automated ML. The presentation will be recorded with video posted to this YouTube Channel: http://bit.ly/2ZybKwI
In this webinar, we will take a look at the Azure Machine Learning Studio and explore the features that it has to offer. We will take a look on how to create a predictive analytic solution and discuss how to deploy the solution as a web service. This will include a case study on Flight Delay Prediction Analysis with Power BI as well.
Azure contains an ever growing suite of products, what tools or products do we have available to remove repetitive tasks from our daily grind. This session is viewed from the perspective of a Cloud/IT Professional, our vision is to automate anything we can using whichever tools we have available.
In this session we will dive into Azure Automation, Microsoft Flow, Azure Functions, Event Grid and more. What are they, how do they relate to each other and what are the pros and cons for using each product. By looking at and understanding how we can leverage the Cloud Automation tools that are available to us today we will be able to work less tomorrow! Warning: Contains code.
Introduction to Machine learning and Deep LearningNishan Aryal
Overview of Machine Learning and Deep Learning. Brief introduction to different types of BI Reporting tools like Power BI, SSMS, Cortana, Azure ML, TenserFlow and other tools.
Slides from my talk at Big Data Conference 2018 in Vilnius
Doing data science today is far more difficult than it will be in the next 5-10 years. Sharing, collaborating on data science workflows in painful, pushing models into production is challenging.
Let’s explore what Azure provides to ease Data Scientists’ pains. What tools and services can we choose based on a problem definition, skillset or infrastructure requirements?
In this talk, you will learn about Azure Machine Learning Studio, Azure Databricks, Data Science Virtual Machines and Cognitive Services, with all the perks and limitations.
Introduction to Azure Machine Learning describes the purpose of Azure Machine Learning, and introduces the main features of Azure Machine Learning Studio.
SharePoint Saturday Calgary 2017 - From SharePoint to Office 365 DevelopmentSébastien Levert
The world around the Office Developer is changing. And for someone with a heavy SharePoint background, it can be somewhat scary to make the move to the cloud. But don't be scared, SharePoint Developer! Become an added-value Office Developer and contribute to maximize the productivity of your enterprise.
The technology space around Productivity has evolved and it has never been that exciting. Your step into the Mobile-First, Cloud-First world will be mindblowing and you will want to stick around for a very long time!
In this session, we will cover every aspect of the new Office 365 Developer paradigm and we will ensure that you can make yourself at home in such a new world. The technologies covered will span from being close to your existing stack (SharePoint Framework, JavaScript) to a set of technologies that are new and that will expand your possibilities (Office 365 Apps, Microsoft Graph, Azure, TypeScript)
This very session will make sure that at the end you get those 3 key takeaways :
- Understand your new role as an Office 365 Developer
- Have a complete overview of the technology stack you need to master in the cloud
- Change the way you will think for your next SharePoint & Office 365 project
Automated machine learning (automated ML) automates feature engineering, algorithm and hyperparameter selection to find the best model for your data. The mission: Enable automated building of machine learning with the goal of accelerating, democratizing and scaling AI. This presentation covers some recent announcements of technologies related to Automated ML, and especially for Azure. The demonstrations focus on Python with Azure ML Service and Azure Databricks.
Building trustworthy and effective AI solutions.
- Many cloud vendor AI services (AWS, GCP, Azure)
- Demo of a workflow with AWS Sagemaker
- What is AI Trust
- What is explainability
- How to add this to a workflow with S3, Sagemaker, Lambda (server less) and Postman
PREDICT THE FUTURE , MACHINE LEARNING & BIG DATADotNetCampus
Scopri come utilizzare Azure Machine Learning, un servizio cloud che consente alle aziende, università, centri di ricerca e sviluppatori di incorporare e sfrutturare nelle loro applicazioni funzionalità di apprendimento automatico e analisi predittiva su enormi set di dati. Tramite Azure ML Studio possiamo creare, testare, attuare e gestire soluzioni di analisi predittiva e apprendimento automatico nel cloud tramite un qualunque web browser. Durante la sessione si darà un saggio attraverso un esempio di analisi predittiva sul Flight Delay.
This is a part of presentation done at Global Azure BootCamp 2017 Mohali Location.
We talked about how to get started with your first data science experiment using Azure Machine Learning Studio.
Integrating Azure Machine Learning and Predictive Analytics with SharePoint O...Bhakthi Liyanage
Windows Azure Machine Learning and Data Analytics platform offers a streamlined experience, from setting up with only a web browser to using drag-and-drop gestures and simple data-flow graphs to set up experiments. Azure Machine Learning Studio features a library of time-saving sample experiments, R and Python packages, and best-in-class algorithms from Microsoft businesses like Xbox and Bing. Learn how the Azure Machine Learning service in the cloud lets you easily build, deploy, and share advanced analytics solutions into your SharePoint platform. Attendees will also gain knowledge on special considerations that should be taken in to account when creating analytical models. The demo will walk you through creating an analytic model in Azure ML studio and consume the model within SharePoint online.
This presentation covers an overview of Analytics and Machine learning. It also covers the Microsoft's contribution in Machine learning space. Azure ML Studio, a SaaS based portal to create, experiment and share Machine Learning Solutions to the external world.
Microsoft DevOps for AI with GoDataDrivenGoDataDriven
Artificial Intelligence (AI) and machine learning (ML) technologies extend the capabilities of software applications that are now found throughout our daily life: digital assistants, facial recognition, photo captioning, banking services, and product recommendations. The difficult part about integrating AI or ML into an application is not the technology, or the math, or the science or the algorithms. The challenge is getting the model deployed into a production environment and keeping it operational and supportable. Software development teams know how to deliver business applications and cloud services. AI/ML teams know how to develop models that can transform a business. But when it comes to putting the two together to implement an application pipeline specific to AI/ML — to automate it and wrap it around good deployment practices — the process needs some effort to be successful.
Automated machine learning (automated ML) automates feature engineering, algorithm and hyperparameter selection to find the best model for your data. The mission: Enable automated building of machine learning with the goal of accelerating, democratizing and scaling AI.
This presentation covers some recent announcements of technologies related to Automated ML, and especially for Azure. The demonstrations focus on Python with Azure ML Service and Azure Databricks.
This presentation is the fourth of four related to ML.NET and Automated ML. The presentation will be recorded with video posted to this YouTube Channel: http://bit.ly/2ZybKwI
In this webinar, we will take a look at the Azure Machine Learning Studio and explore the features that it has to offer. We will take a look on how to create a predictive analytic solution and discuss how to deploy the solution as a web service. This will include a case study on Flight Delay Prediction Analysis with Power BI as well.
Azure contains an ever growing suite of products, what tools or products do we have available to remove repetitive tasks from our daily grind. This session is viewed from the perspective of a Cloud/IT Professional, our vision is to automate anything we can using whichever tools we have available.
In this session we will dive into Azure Automation, Microsoft Flow, Azure Functions, Event Grid and more. What are they, how do they relate to each other and what are the pros and cons for using each product. By looking at and understanding how we can leverage the Cloud Automation tools that are available to us today we will be able to work less tomorrow! Warning: Contains code.
Introduction to Machine learning and Deep LearningNishan Aryal
Overview of Machine Learning and Deep Learning. Brief introduction to different types of BI Reporting tools like Power BI, SSMS, Cortana, Azure ML, TenserFlow and other tools.
Slides from my talk at Big Data Conference 2018 in Vilnius
Doing data science today is far more difficult than it will be in the next 5-10 years. Sharing, collaborating on data science workflows in painful, pushing models into production is challenging.
Let’s explore what Azure provides to ease Data Scientists’ pains. What tools and services can we choose based on a problem definition, skillset or infrastructure requirements?
In this talk, you will learn about Azure Machine Learning Studio, Azure Databricks, Data Science Virtual Machines and Cognitive Services, with all the perks and limitations.
Introduction to Azure Machine Learning describes the purpose of Azure Machine Learning, and introduces the main features of Azure Machine Learning Studio.
SharePoint Saturday Calgary 2017 - From SharePoint to Office 365 DevelopmentSébastien Levert
The world around the Office Developer is changing. And for someone with a heavy SharePoint background, it can be somewhat scary to make the move to the cloud. But don't be scared, SharePoint Developer! Become an added-value Office Developer and contribute to maximize the productivity of your enterprise.
The technology space around Productivity has evolved and it has never been that exciting. Your step into the Mobile-First, Cloud-First world will be mindblowing and you will want to stick around for a very long time!
In this session, we will cover every aspect of the new Office 365 Developer paradigm and we will ensure that you can make yourself at home in such a new world. The technologies covered will span from being close to your existing stack (SharePoint Framework, JavaScript) to a set of technologies that are new and that will expand your possibilities (Office 365 Apps, Microsoft Graph, Azure, TypeScript)
This very session will make sure that at the end you get those 3 key takeaways :
- Understand your new role as an Office 365 Developer
- Have a complete overview of the technology stack you need to master in the cloud
- Change the way you will think for your next SharePoint & Office 365 project
Automated machine learning (automated ML) automates feature engineering, algorithm and hyperparameter selection to find the best model for your data. The mission: Enable automated building of machine learning with the goal of accelerating, democratizing and scaling AI. This presentation covers some recent announcements of technologies related to Automated ML, and especially for Azure. The demonstrations focus on Python with Azure ML Service and Azure Databricks.
Building trustworthy and effective AI solutions.
- Many cloud vendor AI services (AWS, GCP, Azure)
- Demo of a workflow with AWS Sagemaker
- What is AI Trust
- What is explainability
- How to add this to a workflow with S3, Sagemaker, Lambda (server less) and Postman
PREDICT THE FUTURE , MACHINE LEARNING & BIG DATADotNetCampus
Scopri come utilizzare Azure Machine Learning, un servizio cloud che consente alle aziende, università, centri di ricerca e sviluppatori di incorporare e sfrutturare nelle loro applicazioni funzionalità di apprendimento automatico e analisi predittiva su enormi set di dati. Tramite Azure ML Studio possiamo creare, testare, attuare e gestire soluzioni di analisi predittiva e apprendimento automatico nel cloud tramite un qualunque web browser. Durante la sessione si darà un saggio attraverso un esempio di analisi predittiva sul Flight Delay.
Similar to Creating your first data science experiment in azure machine learning studio (20)
This presentation is a part of meetup session delivered in the Microsoft User Group - Chandigarh.
In this meetup we looked into how to deploy and manage Virtual Machines in Microsoft Azure cloud.
This was an advanced session and targeted more towards IT Pro audience. Developers were welcome also.
We covered created virtual machines via ARM template and covered with Virtual Machine Scale Sets with a live demo with Autoscale.
This deck was a part of session delivered at the SharePoint Saturday Dubai event #spsdxb.
In this session we covered the entire process of planning and successfully running SharePoint 2016 in the cloud. We covered topics related to Security, Performance, Scalability, High Availability, Backup & Restore and Disaster Recovery.
Getting started with microsoft cognitive services apiJasjit Chopra
This presentation is a part of meetup that happened on June 17 2017 in Chandigarh. We covered the options for developers to get started with MS Cognitive Services API.
Getting Started with Xamarin App DevelopmentJasjit Chopra
This presentation was a part of Global Azure BootCamp 2017 Mohali session.
In this session we talked about getting started with Xamarin platform and showed its capability of true cross platform with maximized code sharing base.
KeyNote session delivered at the Global Azure Bootamp 2017 in Mohali.
We covered how to get started with Azure and what business use cases are possible to begin with in your journey to the cloud.
How to run blazingly fast word press on azureJasjit Chopra
Part of workshop session hosted at StartHub Nation for Microsoft User Group - Chandigarh. We went through a live workshop where we showed how to install WordPress in a linux VM based on SSD storage.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
2. Agenda
• How to Get Started?
• What is Machine Learning Studio?
• Overview
• Capabilities
• Interface
• Components of an Experiment
• Scenario
• DEMO
8. Components of an Experiment
• The experiment has at least one dataset and one module
• Datasets may be connected only to modules
• Modules may be connected to either datasets or other modules
• All input ports for modules must have some connection to the data
flow
• All required parameters for each module must be set
9. Scenario
Predict the price of an automobile based on different
variables such as make and technical specifications
10. Demo
• Create a model
• Get Data
• Prepare the data
• Define features
• Train the model
• Choose and apply a learning algorithm
• Score and test the model
• Predict new automobile prices
If you've never used Azure Machine Learning Studio before, this session is for you. This session is not for Advanced users. We will not be covering algorithms here.
Quick Evaluation: https://studio.azureml.net/Home/Anonymous
Free Workspace: https://studio.azureml.net/Home
Standard Workspace: https://azure.microsoft.com/en-us/documentation/articles/machine-learning-create-workspace
PROJECTS - Collections of experiments, datasets, notebooks, and other resources representing a single project
EXPERIMENTS - Experiments that you have created and run or saved as drafts
WEB SERVICES - Web services that you have deployed from your experiments
NOTEBOOKS - Jupyter notebooks that you have created
DATASETS - Datasets that you have uploaded into Studio
TRAINED MODELS - Models that you have trained in experiments and saved in Studio
SETTINGS - A collection of settings that you can use to configure your account and resources.