Clock
Test duration:
60
min
Notes
No. of questions:
22
Tie
Level of experience:
Entry/Mid/Expert

ML Engineer with Python Test

iMocha's Machine Learning coding test enables recruiters and hiring managers to assess Python programming skills for Machine Learning. Machine tests for python can help hire Data Scientists, Data Science engineers, Data Science developers, Data Science associates, Data Analysts, and Machine Learning engineers. Our test can help you reduce hiring costs by 40%.

28712
+
Candidates
Assessed
123
+
Organizations Served
Fujitsu
Paypal
Capgemini
Deloitte
Coupa
UN Logo
Vanguard
EY Logo
About

ML Engineer with Python Test

Machine learning with Python is a data science technique in which programmers work with machine learning algorithms to put data into practical work. Machine Learning with Python mainly focuses on developing various computer programs that can help the programmer change it when exposed to new data.

The machine learning coding test helps recruiters and hiring managers assess candidates’ Python programming skills for machine learning. Machine test for Python is designed by experienced Subject Matter Experts (SMEs) to evaluate and hire machine learning engineers as per industry standards.

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How it works

Test Summary

Machine learning coding test helps to screen the candidates who possess traits as follows: 

  • Ability to write code with Python libraries that support machine learning algorithms
  • Knowledge of supervised learning, unsupervised learning, and reinforcement learning
  • Understanding concepts like NumPy with Python, machine learning with SciKit Learn, linear regression, K Nearest Neighbors, K Means clustering, decision trees, random forests, support vector machines
  • Excellent experience in Natural Language Processing, Neural Networks, and Deep Learning

Machine test for Python for machine learning with python contains a coding simulator that will automatically evaluate and provide a score for the candidate’s written codes by compiling multiple test cases that generate discrete output. You will also get a detailed report for each test case execution, execution time, and execution memory usage for the program written by the candidate. The Code-Replay feature records the coding screen of the candidate so that the reviewer can understand the coding and thinking patterns of the candidate.


This Machine Learning coding test may contain coding questions and innovative AI-LogicBox (pseudo coding platform) questions to assess a candidate’s coding skills in a fun and quick way.

Test Duration
60
No. of Questions
22
Level of Expertise
Entry/Mid/Expert
Useful for hiring
  • Data Scientists
  • Data Science Engineer
  • Data Science Developer
  • Data Science Associate
  • Data Analyst
  • Machine Learning Engineer
Topics Covered
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Classification and Regression Algorithms

The machine learning coding test evaluates the candidate&

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Sample Question
Choose from our 100,000+ questions library or add your own questions to make powerful custom tests.

Question types :

Multiple Option

Topic:

Difficulty:

Hard


Q 1. You have been asked to train « Naive Bayes model for spam detection dataset

Using Python command, what wil you add in the given code at XXXX to deciore, it and train your modal for the given dataset?

import numpy os np

X= nporroyll 3. 2b[1 21 [2.21.[3,21)
Y= nporray(fi.a,a.1))

XXXX

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

from skinamnaive_bayas import

Gaussianna

otf = Gaussianne()

ceataie(x ¥)

Question types :

Multiple Option

Topic:

Machine teaming

Difficulty:

Hard


Q 1. Q2 Lets assume that you have 6 Pandas DataFrome(af) in the below tole.

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074

When the following commend is executed, what hoppens to the DatoFrome?

df= defiinat()
Y= nporray(fi.a,a.1))

Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
Index Code Open High
0 AAPL 19877 70074
1 AAPL 19877 70074
2 AAPL 19877 70074
3 AAPL 19877 70074
4 AAPL 19877 70074
it gives an error becouse of the third row which has on empty string.
None of these

Question types :

Multiple Option

Topic:

Classification and Regression Algorithms - Bayesian Parameter Selection

Difficulty:

Hard

Question:

In which of the following conditions will the maximum a-posteriori hypothesis be equal to the maximum likelihood estimate hypothesis?


Options

  • When the parameter θ has a lognormal distribution.
  • When the parameter θ has an exponential distribution.
  • When the parameter θ has a uniform distribution.
  • None of the options.
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FAQ
What is Data Science?
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