Test Machine Learning Algorithms
Test Machine Learning with answers to assess your knowledge and prepare for job interviews. Assess your technical level in 20 minutes.
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Machine Learning
Machine Learning is a field of study of artificial intelligence that uses mathematical and statistical approaches to give computers the ability to "learn" from data, i.e. to improve their performance in solving tasks without being explicitly programmed for each one. More broadly, it concerns the design, analysis, optimization, development and implementation of such methods.
About the MCQ "Machine Learning Algorithms"
There are several algorithms for implementing prediction models. The objective of this MCQ is to check your knowledge around the most used algorithms in the field of Machine Learning. It contains basic questions on the following topics:
- Simple regression algorithms and logistic regression algorithms.
- Decision tree type algorithms.
- Type algorithms and Random Forest.
- Support Vector Machine (SVM) type algorithms.
- Clustering models like KMeans.
- The notions of dimensionality reduction with the method of principal component analysis.
- Neural networks and the notions of training a model.
Test author : Madjid Khichane
About the author, Madjid KHICHANE.
After an engineering degree in Computer Science obtained at Mouloud Mammeri University in Tizi-Ouzou in Algeria then a Master's degree in Artificial Intelligence obtained at Paris 5 University (René Descartes), Madjid KHICHANE defended his PhD in Artificial Intelligence in collaboration between Claude Bernard Lyon 1 University and IBM.
This doctoral thesis gave rise to algorithmic innovations in the field of reinforcement learning which are now published in leading international conferences.
Madjid has held positions as an expert in artificial intelligence and expert in Data Science within major international groups in the field of computer technologies and particularly in the field of Data Science.
Sample question
From which elements is the error calculated during back propagation in a neural network?
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