Learn R Programming Offline vs Azure AI Fundamentals Quiz Uso & Estadísticas

Learn R Programming Offline & become a job-ready R programmer. R Language was designed by statisticians. R Language is specialized for statistical computing, statistical data analytics Machine learning, and deep learning, Web applications using RShinyand. As technology is improving, the data companies or research institutions collect has become more and more complex, and R has been adopted by many as the language of choice to analyze data. R is great for machine learning, data visualization and analysis, and some areas of scientific computing. This app contains all the major topics of R Programming with Excellent Code Examples and Projects. Why you should Learn R Programming? R Programming in Open Source: R is free, open-source software. It's plug and play, install R once, and start having fun with it. What more? You can even modify the code and add your own innovations to it. R language has no license restrictions as it is issued under the GNU. R is Cross-Platform Compatible: One of the biggest advantages of R is that you can run R on several operating systems and varied Software/Hardware. Large Community: Let’s say you are working on a financial project to find out how many of the credit card transactions are fraudulent and reach a roadblock while building the classification model. Thankfully, R boasts of a huge community to tap into whenever you need help. So, you can always seek help from people who have worked on similar projects. Interactive Web apps: Ever wondered if there is a tool that helps in creating stunning web applications directly from your data analysis software? R provides a package called shiny, just for that. With the help of shiny, you can create interactive web pages and impressive dashboard designs directly from your R Console. High Paying Jobs: n a Survey done by Dice Tech of over 18,000 technology professionals, the highest-paid IT skill was R programming. R language skills attract median salaries in excess of $120,000. With R language as a skill-set, one can find jobs such as: 1- Data Analyst 2- Data Scientist 3- Quantitative Analyst 4- Financial Analyst So if you Like our effort please rate this app or comment below if you want to give us any suggestions or ideas. Thanks Privacy Policy https://www.freeprivacypolicy.com/privacy/view/e04d63ec5cc622ecbe51e2f7ec31dd96
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Skills Measured: Describe Artificial Intelligence workloads and considerations (15-20%) Identify features of common AI workloads Identify prediction/forecasting workloads Identify features of anomaly detection workloads Identify computer vision workloads Identify natural language processing or knowledge mining workloads Identify conversational AI workloads Identify guiding principles for responsible AI Describe considerations for fairness in an AI solution Describe considerations for reliability and safety in an AI solution Describe considerations for privacy and security in an AI solution Describe considerations for inclusiveness in an AI solution Describe considerations for transparency in an AI solution Describe considerations for accountability in an AI solution Describe fundamental principles of machine learning on Azure (30- 35%) Identify common machine learning types Identify regression machine learning scenarios Identify classification machine learning scenarios Identify clustering machine learning scenarios Describe core machine learning concepts Identify features and labels in a dataset for machine learning Describe how training and validation datasets are used in machine learning Describe how machine learning algorithms are used for model training Select and interpret model evaluation metrics for classification and regression Identify core tasks in creating a machine learning solution Describe common features of data ingestion and preparation Describe feature engineering and selection Describe common features of model training and evaluation Describe common features of model deployment and management Describe capabilities of no-code machine learning with Azure Machine Learning studio Automated ML UI Azure Machine Learning designer Describe features of computer vision workloads on Azure (15-20%) Identify common types of computer vision solution: Identify features of image classification solutions Identify features of object detection solutions Identify features of optical character recognition solutions Identify features of facial detection, facial recognition, and facial analysis solutions Identify Azure tools and services for computer vision tasks Identify capabilities of the Computer Vision service Identify capabilities of the Custom Vision service Identify capabilities of the Face service Identify capabilities of the Form Recognizer service Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%) Identify features of common NLP Workload Scenarios Identify features and uses for key phrase extraction Identify features and uses for entity recognition Identify features and uses for sentiment analysis Identify features and uses for language modeling Identify features and uses for speech recognition and synthesis Identify features and uses for translation Identify Azure tools and services for NLP workloads Identify capabilities of the Text Analytics service Identify capabilities of the Language Understanding service (LUIS) Identify capabilities of the Speech service Identify capabilities of the Translator Text service Describe features of conversational AI workloads on Azure (15-20%) Identify common use cases for conversational AI Identify features and uses for webchat bots Identify common characteristics of conversational AI solutions Identify Azure services for conversational AI Identify capabilities of the QnA Maker service Identify capabilities of the Azure Bot service
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Learn R Programming Offline VS.
Azure AI Fundamentals Quiz

11iciembre d, 2024