10+ Machine Learning Engineer Interview Questions and Answers for Freshers

ML algorithms are techniques used to train models to make predictions or decisions based on data.

• Supervised learning algorithms: Linear regression, logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors

• Unsupervised learning algorithms: K-means clustering, hierarchical clustering, principal component analysis

• Reinforcement learning algorithms: Q-learning, SARSA

• Deep learning algorithms: Convolutional neural networks, recurrent neural ne...read more

Use natural language processing techniques to detect and identify medicines on a doctor's prescription.

• Preprocess the text by removing noise and irrelevant information.

• Tokenize the text to break it down into individual words or characters.

• Use a language model or dictionary to match the tokens with known medicines.

• Apply machine learning algorithms like NER (Named Entity Recognition) to identify medicine names.

• Consider context and surrounding words to improve accuracy of predic...read more

Naive Bayes is a probabilistic algorithm that uses Bayes' theorem to classify data based on prior knowledge.

• Naive Bayes assumes that all features are independent of each other.

• It is commonly used for text classification and spam filtering.

• There are three types of Naive Bayes classifiers: Gaussian, Multinomial, and Bernoulli.

• It is a fast and simple algorithm that works well with high-dimensional datasets.

• Naive Bayes can handle missing data and is not affected by irrelevant fea...read more

The answer depends on the size of the plane and the size of the tennis balls.

• The size of the plane and the size of the tennis balls are important factors to consider.

• The packing method used to fit the tennis balls in the plane also matters.

• Assuming a standard commercial plane and tennis ball size, approximately 50,000 tennis balls can fit in the plane.

Regression is a statistical method used to analyze the relationship between a dependent variable and one or more independent variables.

• Regression is used to predict continuous numerical values.

• It helps in identifying the strength and direction of the relationship between variables.

• Linear regression is a common type of regression used to model the relationship between two variables.

• Examples of regression include predicting housing prices based on square footage and predicting ...read more

Sound classification can be done using machine learning algorithms to analyze audio data and classify it into different categories.

• Preprocess the audio data by extracting relevant features such as MFCCs, spectrograms, or mel spectrograms.

• Split the data into training and testing sets to train the machine learning model.

• Choose a suitable classification algorithm such as SVM, Random Forest, or CNN for audio data.

• Train the model on the training data and evaluate its performance o...read more

Accuracy paradox is a phenomenon where high accuracy can be achieved even with a flawed model.

• Accuracy paradox occurs when the accuracy of a model is high but the model is flawed.

• It happens when the dataset is imbalanced and the model predicts the majority class accurately while ignoring the minority class.

• For example, a model predicting that all patients are healthy when only 5% of them are sick can have high accuracy but is not useful in practice.

OOPs stands for Object-Oriented Programming and its 4 pillars are Inheritance, Encapsulation, Abstraction, and Polymorphism.

• Inheritance allows a class to inherit properties and behavior from another class.

• Encapsulation restricts access to certain components of an object, protecting its integrity.

• Abstraction hides complex implementation details and only shows the necessary features.

• Polymorphism allows objects to be treated as instances of their parent class, enabling flexibili...read more