Purpose

This assessment is designed for freshers with 0–1 years of experience in the IT, Software & ITeS industry, specifically targeting the role of Machine Learning Engineer. Its main goal is to evaluate foundational knowledge and skills in machine learning concepts and techniques.

Overview

The test is structured to assess foundational machine learning skills suitable for entry-level roles, particularly Machine Learning Engineers. It evaluates core traits such as analytical thinking, problem-solving, and understanding of machine learning principles. The questions cover a broad range of topics, including feature scaling, kernel functions, ensemble methods, and data preprocessing. The assessment aims to identify candidates who possess the necessary theoretical knowledge and practical understanding to begin a career in machine learning. It is designed to ensure that candidates can apply basic machine learning techniques and are familiar with essential algorithms and evaluation metrics.

• Industry: IT, Software & ITeS
• Level: Fresher
• Tag: Machine Learning Engineer
• Total Questions: 25

Skills

• Feature Scaling
• Kernel Functions
• Cross-Validation
• Ensemble Methods
• One-Hot Encoding
• Non-Linear Algorithms
• Precision in Classification
• Neural Network Optimization
• Clustering
• Gradient Descent
• Regularization
• Decision Trees
• Data Handling
• Bias and Variance
• Confusion Matrix
• Dimensionality Reduction
• Regression Metrics
• Overfitting
• Activation Functions
• Binary Classification
• Data Preprocessing

Ideal Roles

• Machine Learning Engineer
• Data Scientist
• AI Engineer
• Data Analyst