Online ili uživo, obučavanje Supervised Learning-a pod vođstvom instruktora demonstrira kroz interaktivnu praksu uživo kako koristiti tehnike nadzorovanog mašinskog učenja za obučavanje modela, predviđanje i efikasnu analizu obrazaca podataka.
Obuka iz nadzorovanog učenja dostupna je kao "online uživo" ili "uživo na licu mesta". Online obuka uživo (poznata i kao "daljinska obuka uživo") realizuje se putem interaktivnog, daljinskog radnog okruženja. Obuka uživo na licu mesta može se realizovati lokalno na prostorijama klijenta u Belgrade ili u korporativnim centrima za obuku NobleProg-a u Belgrade.
Nadzorovano učenje poznato je i kao nadzorovano mašinsko učenje.
NobleProg -- Vaš lokalni provajder obuka
Green Heart Complex
Bulevar Milutina Milankovića 11b, Belgrade 11070, Belgrade, Serbia
Strategically located at Bulevar Milutina Milankovića 11b in Belgrade, Serbia, the Green Heart Complex stands as a prominent landmark in one of the country's most dynamic areas. This prestigious address places the complex within close proximity to key government buildings, cultural institutions, embassies, and major shopping centers, making it an ideal location for business and administrative activities.
Its prime position on Bulevar Milutina Milankovića offers excellent accessibility and visibility, ensuring convenient connections to the heart of Belgrade's commercial and residential districts. The complex itself serves as a vital hub, providing modern facilities and services to support a diverse range of professional and commercial needs.
From this strategic base, occupants and visitors benefit from proximity to Belgrade's vibrant urban life, including dining, entertainment, and transportation options. The Green Heart Complex represents a significant asset in the city's ongoing development, contributing to the efficiency and functionality of Belgrade's central business district.
This instructor-led, live training in Belgrade (online or onsite) targets participants with varying levels of expertise who wish to leverage Google's AutoML platform to build customized chatbots for various applications.
By the end of this training, participants will be able to:
Understand the fundamentals of chatbot development.
Navigate the Google Cloud Platform and access AutoML.
Prepare data for training chatbot models.
Train and evaluate custom chatbot models using AutoML.
Deploy and integrate chatbots into various platforms and channels.
Monitor and optimize chatbot performance over time.
This instructor-led, live training in Belgrade (online or onsite) is designed for intermediate-level professionals who aim to apply AI-driven predictive maintenance techniques in semiconductor manufacturing to improve production efficiency and reduce unexpected equipment failures.
By the end of this training, participants will be able to:
Deploy AI models to predict equipment failures in semiconductor production.
Analyze maintenance data to uncover patterns and trends that signal potential issues.
Incorporate AI-driven predictive maintenance into current manufacturing workflows.
Lower downtime and maintenance expenses via proactive equipment management.
This instructor-led, live training in Belgrade (online or onsite) is designed for beginner-level professionals who wish to understand and apply AI technologies within the semiconductor manufacturing industry.
By the end of this training, participants will be able to:
Understand the basic principles of AI and their application in semiconductor manufacturing.
Identify areas within semiconductor manufacturing where AI can be effectively implemented.
Utilize AI tools and techniques to enhance production efficiency and quality control.
Implement basic AI models to optimize manufacturing processes.
This instructor-led, live training in Belgrade (online or onsite) is aimed at intermediate-level data analysts who wish to learn how to use RapidMiner to estimate and project values and utilize analytical tools for time series forecasting.
By the end of this training, participants will be able to:
Learn to apply the CRISP-DM methodology, select appropriate machine learning algorithms, and enhance model construction and performance.
Use RapidMiner to estimate and project values, and utilize analytical tools for time series forecasting.
This instructor-led, live training in Belgrade (online or onsite) offers an introduction to the fields of pattern recognition and machine learning. It covers practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.
By the end of this training, participants will be able to:
Apply core statistical methods to pattern recognition.
Use key models like neural networks and kernel methods for data analysis.
Implement advanced techniques for complex problem-solving.
Improve prediction accuracy by combining different models.
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