You will get a fully functional and deployed Azure Machine Learning Model

Aimé T.
Aimé T.

Let a pro handle the details

Buy Machine Learning services from Aimé, priced and ready to go.

You will get a fully functional and deployed Azure Machine Learning Model

Aimé T.
Aimé T.

Let a pro handle the details

Buy Machine Learning services from Aimé, priced and ready to go.

Project details

You will get as promised a fully functional Azure Machine Learning Deployment. It can be produced in three ways either AutoML or HyperDrive or Both. Then saved as Pickle or ONYX or as a ACI or AKS deployment. Especially useful for but not excluding complex BigData Modelling.
Machine Learning Tools
Azure Machine Learning, Keras, NLTK, NumPy, NVIDIA AI Platform, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, R, Scrapy, SPSS, SQL, TensorFlow, Theano, XGBoost
What's included
Service Tiers Starter
$100
Standard
$200
Advanced
$300
Delivery Time 1 day 3 days 5 days
Number of Revisions
123
Number of Scenarios
123
Number of Graphs/Charts
123
Model Validation/Testing
-
Model Documentation
-
-
Data Source Connectivity
Source Code
Aimé T.

About Aimé

Aimé T.
Generative AI | Microsoft Certified | IBM Ceritied | FRSS | MRSC |
Alta, Sweden - 10:15 pm local time
I have now finished a Data Analyst Traineeship with Hi-Tech Plus in London. I gained exposure to many business datasets, where I would deliver high quality analysis and report the analysis using Excel, Power BI, Google Data Studio, Python, Kibana and MS Office. I also excelled at web scraping along with some sentiment analysis in Python. I am also Microsoft Certified. Currently working as a Language Data Analyst at Transperfect.

Steps for completing your project

After purchasing the project, send requirements so Aimé can start the project.

Delivery time starts when Aimé receives requirements from you.

Aimé works on your project following the steps below.

Revisions may occur after the delivery date.

Python script

A functional script for how the data is mind and ultimately turned into a model

azureML script

establishing the working environment for the data and prior script's consumption, and exposure to AutoML, and HyperDrive to access wanted model parameter ranges and/or accuracy's. All this for saving and/or deployment.

Review the work, release payment, and leave feedback to Aimé.