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ML Engineer with Python

Screens candidates with Python skills in NumPy, SciPy, Scikit-learn, and expertise in supervised, unsupervised, reinforcement learning, and various algorithms including linear regression, K-nearest neighbors, decision trees. Proficient in NLP, neural networks, and deep learning.

Category: Technical Expertize Level:

Skills Required

  • Classification and Regression Algorithms
  • Bootstrapping
  • Data Cleaning
  • Machine Learning Coding
  • Scikit-learn
  • Types of Machine Learning

About the ML Engineer with Python Assessment

Machine learning with Python is a data science technique that uses Python programming language to develop and apply machine learning algorithms to data. Machine learning coding tests are used to screen candidates who have the following skills: • Ability to write code with Python libraries that support machine learning algorithms, such as NumPy, SciPy, and Scikit-learn. • Knowledge of supervised learning, unsupervised learning, and reinforcement learning. • Understanding of concepts like linear regression, K nearest neighbors, K-means clustering, decision trees, random forests, and support vector machines. • Excellent experience in natural language processing, neural networks, and deep learning.