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About the test:

The pre-employment machine learning assessment test evaluates a candidate's understanding of machine learning fundamentals like feature engineering, regression, variance, conditional probability, clustering, decision trees, nearest neighbors, Naïve Bayes, bias and overfitting. The test also assesses them on their ability to collect and prepare the dataset, train a model, evaluate the model, and iteratively improve the model's performance.

Covered skills:

  • Linear Regression
  • Classification
  • Gradient Descent
  • Accuracy Matrix
See all covered skills

9 reasons why
9 reasons why

Adaface Machine Learning Assessment Test is the most accurate way to shortlist Machine Learning Engineers



Reason #1

Tests for on-the-job skills

The Machine Learning Assessment Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates.

The pre-employment machine learning assessment test screens candidates for the typical skills recruiters look for Machine Learning developer roles:

  • Experience designing, developing, and researching Machine Learning models
  • Deep understanding of fundamental data structures and data modeling
  • Expertise in math, probability and statistics
  • Ability to write robust code
  • Experience with machine learning frameworks (like Keras, PyTorch, Tensorflow etc.) and libraries (like scikit-learn, Numpy, Pandas etc.)
  • Ability to choose hardware for running an ML model with the needed latency

The insights generated from this assessment can be used by recruiters and hiring managers to identify the best candidates for Machine Learning developer roles. Anti-cheating features enable you to be comfortable with conducting assessments online. The Machine Learning Assessment Test is ideal for helping recruiters identify which candidates have the skills to do well on the job.

Reason #2

No trick questions

Traditional assessment tools use trick questions and puzzles for the screening, which creates a lot of frustration among candidates about having to go through irrelevant screening assessments.

The main reason we started Adaface is that traditional pre-employment assessment platforms are not a fair way for companies to evaluate candidates. At Adaface, our mission is to help companies find great candidates by assessing on-the-job skills required for a role.

Why we started Adaface ->
Reason #3

Non-googleable questions

We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

To tylko niewielka próbka z naszej biblioteki ponad 10 000 pytań. Rzeczywiste pytania dotyczące tego Machine Learning Assessment Test będzie nieobowiązany.

🧐 Question

Hard

n-gram generator
Solve
Our newest machine learning developer want to write a function to calculate the n-gram of any text. An N-gram means a sequence of N words. So for example, "black cats" is a 2-gram, "saw black cats" is a 3-gram etc. The 2-gram of the sentence "the big bad wolf fell down" would be [["the", "big"], ["big", "bad"], ["bad", "wolf"], ["wolf", "fell"], ["fell", "down"]]. Can you help them select the correct function for the same?
 image
🧐 Question🔧 Skill

Hard

n-gram generator
2 mins
Machine Learning
Solve
🧐 Question🔧 Skill💪 Difficulty⌛ Time
n-gram generator
Machine Learning
Hard2 mins
Solve
Reason #4

1200+ customers in 75 countries

Brandon

With Adaface, we were able to optimise our initial screening process by upwards of 75%, freeing up precious time for both hiring managers and our talent acquisition team alike!


Brandon Lee, Head of People, Love, Bonito

Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment Machine Learning Assessment Test in your hiring process is that it is an elimination tool, not a selection tool. In other words: you want to use the test to eliminate the candidates who do poorly on the test, not to select the candidates who come out at the top. While they are super valuable, pre-employment tests do not paint the entire picture of a candidate’s abilities, knowledge, and motivations. Multiple easy questions are more predictive of a candidate's ability than fewer hard questions. Harder questions are often "trick" based questions, which do not provide any meaningful signal about the candidate's skillset.

Reason #6

1 click candidate invites

Email invites: You can send candidates an email invite to the Machine Learning Assessment Test from your dashboard by entering their email address.

Public link: You can create a public link for each test that you can share with candidates.

API or integrations: You can invite candidates directly from your ATS by using our pre-built integrations with popular ATS systems or building a custom integration with your in-house ATS.

Reason #7

Detailed scorecards & comparative results

Reason #8

High completion rate

Adaface tests are conversational, low-stress, and take just 25-40 mins to complete.

This is why Adaface has the highest test-completion rate (86%), which is more than 2x better than traditional assessments.

Reason #9

Advanced Proctoring


About Machine Learning Developer Roles

Machine learning (ML) is a subset of artificial intelligence (AI) that enables software programmes to grow increasingly effective at predicting outcomes without explicitly programming them to do so. Machine learning algorithms estimate new output values by using past data as input.

A machine learning (ML) developer is an expert in training models with data. Following that, the models are utilised to automate activities such as image classification, speech recognition, and market forecasting.

A machine learning developer creates a solution that is unique to each situation. The only way to get the best results is to thoroughly process the data and use the appropriate algorithm for the current situation.

Typical Machine Learning Developer/Engineer responsibilities include:

  • Understanding corporate objectives and creating models to assist them be accomplished, as well as measurements to track their success
  • Managing available resources such as hardware, data, and staff in order to meet deadlines
  • Analyzing the ML algorithms that may be utilised to tackle a particular problem and evaluating them based on their likelihood of success
  • Exploring and visualising data
  • Verifying and/or assuring data quality through data cleansing
  • Locating public datasets that might be utilised for training
  • Developing Validation Methodologies
  • Specifying the preprocessing or feature engineering that will be performed on a given dataset
  • Creating pipelines for data augmentation
  • Analyzing the model's flaws and devising solutions to overcome them

What roles can I use the Machine Learning Assessment Test for?

  • Machine Learning Engineer
  • Machine Learning Developer

What topics are covered in the Machine Learning Assessment Test?

Training Data & Test Data
Bias-Variance Tradeoff
Overfitting and Underfitting
Classification
Statistics
Feature Engineering
Probability
Data Preparation
Regularization
Cross-Validation
Uni-variate Analysis
Bi-variate Analysis
Multivariate Analysis
Inferential Statistical Analysis
Outliers
Scaling (Standardization, Normalization)
Pre-Model Building
Model Splitting
Supervised Learning Algorithms
Regression: Linear Regression, Logistic Regression
Decision Tree
K-Nearest Neighbors
Naive Bayes
Support Vector Machines
Unsupervised Learning Algorithms
Segmentation
K-Means Clustering
Agglomerative Hierarchical Clustering
Dimensionality Reduction
Principal Component Analysis
Model Validation
Hyper Parameter Tuning
Singapore government logo

The hiring managers felt that through the technical questions that they asked during the panel interviews, they were able to tell which candidates had better scores, and differentiated with those who did not score as well. They are highly satisfied with the quality of candidates shortlisted with the Adaface screening.


85%
reduction in screening time

Machine Learning Online Test FAQs

Jakie pytania zawiera test uczenia maszynowego?

Ten test uczenia maszynowego przed zatrudnieniem składa się z pytań opartych na scenariuszach, które wymagają od kandydatów wykazania ich zdolności do:

  • Przygotuj dane do algorytmów uczenia maszynowego
  • Użyj algorytmów ML, takich jak regresja logistyczna, maszyny wektorowe wsparcia, drzewa decyzyjne i losowe lasy do klasyfikacji
  • Buduj algorytmy grupowania
  • Zaproponuj najbardziej odpowiedni algorytm dla określonego przypadku użycia
  • Oszacuj wydajność algorytmów uczenia się

Czy ten test lub ocena można wykorzystać do ról starszych inżynierów uczenia maszynowego?

W przypadku starszych inżynierów uczenia maszynowego możesz poprosić o niestandardowy test. W ciągu 48 godzin nasi eksperci merytoryczni dostosują ocenę zgodnie z opisem stanowiska i poziomem stażu pracy. Typowy test dla wyższych ról, oprócz podstaw, test koncentruje się na testowaniu zdolności kandydata na:

  • Struktura projektów ML
  • Zidentyfikuj niedociągnięcia różnych algorytmów uczenia maszynowego
  • Zaprojektuj proces czyszczenia danych i etykietowania danych
  • Wybierz odpowiednie wskaźniki oceny, aby poprawić wydajność modelu
  • Oceń wpływ wydajności sprzętu na algorytmy uczenia maszynowego

Czy mogę połączyć wiele umiejętności w jedną niestandardową ocenę?

Tak, absolutnie. Oceny niestandardowe są konfigurowane na podstawie opisu stanowiska i będą zawierać pytania dotyczące wszystkich określonych umiejętności, które określasz.

Czy masz jakieś funkcje anty-cheatingowe lub proktorowe?

Mamy następujące funkcje anty-cheatingowe:

  • Pytania o niezgodne z nich
  • Proctoring IP
  • Proctoring Web
  • Proctoring kamery internetowej
  • Wykrywanie plagiatu
  • Bezpieczna przeglądarka

Przeczytaj więcej o funkcjach Proctoring.

Jak interpretować wyniki testów?

Najważniejsze, o czym należy pamiętać, jest to, że ocena jest narzędziem eliminacyjnym, a nie narzędziem wyboru. Ocena umiejętności jest zoptymalizowana, aby pomóc Ci wyeliminować kandydatów, którzy nie są technicznie zakwalifikowani do roli, nie jest zoptymalizowana, aby pomóc Ci znaleźć najlepszego kandydata do tej roli. Dlatego idealnym sposobem na wykorzystanie oceny jest podjęcie decyzji o wyniku progowym (zwykle 55%, pomagamy Ci porównać) i zaprosić wszystkich kandydatów, którzy wyniki powyżej progu na następne rundy wywiadu.

Do jakiego poziomu doświadczenia mogę użyć tego testu?

Każda ocena Adaface jest dostosowana do opisu stanowiska/ idealnego kandydującego osobowości (nasi eksperci przedmiotu będą podejmować właściwe pytania dotyczące oceny z naszej biblioteki ponad 10000 pytań). Ocenę tę można dostosować do dowolnego poziomu doświadczenia.

Czy każdy kandydat otrzymuje te same pytania?

Tak, znacznie ułatwia porównanie kandydatów. Opcje pytań MCQ i kolejność pytań są losowe. Mamy funkcje anty-cheating/proctoring. W naszym planie korporacyjnym mamy również możliwość tworzenia wielu wersji tej samej oceny z pytaniami o podobnych poziomach trudności.

Jestem kandydatem. Czy mogę spróbować testu ćwiczeniowego?

Nie. Niestety, w tej chwili nie wspieramy testów ćwiczeń. Możesz jednak użyć naszych przykładowych pytań do ćwiczeń.

Jaki jest koszt korzystania z tego testu?

Możesz sprawdzić nasze Plany cenowe.

Czy mogę dostać bezpłatny proces?

Tak, możesz zarejestrować się za darmo i podgląd tego testu.

Właśnie przeniosłem się do płatnego planu. Jak mogę poprosić o ocenę niestandardową?

Oto szybki przewodnik dotyczący jak poprosić o ocenę niestandardową na Adaface.

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40 min tests.
No trick questions.
Accurate shortlisting.
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