Modern business process mining (BPM) tools enable to generate a copy (aka digital twin) of your business process, run simulations and analyze what would happen if the conditions change (what-if analysis). This article is a step-by-step example of how to do it in Apromore — one of the most advanced BPM tools available.
A pre-trained model is a saved machine learning model that was previously trained on a large dataset (e.g all the articles in the Wikipedia) and can be later used as a “program” that carries out an specific task (e.g finding the sentiment of the text).
Hugging Face is a great resource for pre-trained language processing models. That said, most of the available models are trained for popular languages (English, Spanish, French, etc.). Luckily, many smaller languages have pre-trained models available for translation task. Here, I’m going to demonstrate how one could use available models by:
This article walks you through two examples: how to parallelize 1.) Python functions and 2.) the inference (usage) of machine learning models.
By default, Python is using a single core processing unit (CPU). Various techniques and tools can be used to parallelize computations (make the code run on multiple CPUs). Here, I use Ray, which is a framework for scaling computations on a single machine (your laptop) or on a large cluster…
Lähitulevikus hakkavad digitaalsed Agendid toimetama meie töökeskkonnas, võttes vastu otsuseid ja teostades samme igapäevaste ülesannete täitmiseks. Inimspetsialisti roll ei kao, kuid see muutub olulisel määral. Käesolev artikkel annab ühe võimaliku versiooni meie rollist digitaalsete agentide kõrval. Antud artikli kontekstis on digitaalne agent defineeritud kui programm, mida treenitakse stiimulõppe (reinforcement learningI) abil ja mille eesmärgiks on teha iseseisvalt optimaalseid otsuseid.
Meie tehnoloogiline võimekus on jõudnud tasemele, kus arvuti suudab võita inimeksperte nii males, Go’s kui ka erinevais videomängudes. Parimad neist programmidest on treenitud stiimulõppe (reinforcement learning) algoritmidega. See on masinõppe liik, kus on programmeeritud järgmised elemendid:
This tutorial gives you step-by-step introduction of how to get started with Azure Personalizer. This tutorial has been updated on 07.11.2019. Please remember that the service is under active development and might not match this tutorial in the future.
To start, you need an Azure subscription. An Azure subscription allows you to manage storage, compute, and other assets in the Azure cloud. You can create a new subscription or access existing subscription information from the Azure portal. Alternatively, ask IT admin or your manager to create a subscription for you.
Azure platform has a concept of resources which means a…
This is a step-by-step guide of how to create a computer vision model with Azure Custom Vision Service without writing a single line of code. After finishing, you’ll be able to set up the service, train a machine learning model, evaluate the performance of the model and publish your freshly created machine learning solution.
If you don’t have an account, ask IT admin or your manager to enable the service for you.
Azure platform has a concept of resources which means a specific service. In order to create a Custom Vision resource, log in to your Azure Cloud account and:
Computer Vision is a branch of artificial intelligence which aims to extract information from digital images and videos. The most common functionalities of Computer Vision are:
The following figure (Figure 1) shows an example of using Computer Vision for identifying and classifying objects. In this case, the model successfully realized that there is Power Line & Electrical Supply on the image and that it is a Public utility. …
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