Flip Robo Technologies Interview Questions, Process, and Tips

A reusable piece of UI that can be composed with other components to form a complete UI.

• Components are the building blocks of React applications.

• They can be either functional or class-based.

• They can have state, props, and lifecycle methods.

• They can be reused and composed to create complex UIs.

• Examples include buttons, forms, and navigation menus.

The map method creates a new array with the results of calling a provided function on every element in the original array.

• The map method does not modify the original array.

• The provided function takes three arguments: currentValue, index, and array.

• The map method returns a new array with the same length as the original array.

• Example: const numbers = [1, 2, 3]; const doubledNumbers = numbers.map(num => num * 2); // [2, 4

useState is a hook in React that allows functional components to have state.

• useState is used to manage state in functional components

• It returns an array with two elements: the current state value and a function to update it

• Example: const [count, setCount] = useState(0);

• The initial state value is passed as an argument to useState

forEach and map are array methods in JavaScript. forEach executes a provided function once for each array element. Map creates a new array with the results of calling a provided function on every element in the calling array.

• forEach does not return anything, it just iterates over the array and executes the provided function for each element.

• Map returns a new array with the results of calling a provided function on ever...read more

Correlation is a statistical measure that describes the relationship between two variables.

• Correlation ranges from -1 to 1, where 1 indicates a perfect positive relationship, -1 indicates a perfect negative relationship, and 0 indicates no relationship.

• Correlation does not imply causation, meaning just because two variables are correlated, it does not mean that one causes the other.

• Examples of correlation include the r...read more

Normalization is the process of scaling and standardizing data to have a consistent range.

• Normalization helps in comparing different features on the same scale.

• Common normalization techniques include Min-Max scaling and Z-score normalization.

• Example: Scaling age and income variables to a range of 0 to 1.

I have worked on a project predicting housing prices using regression models on Kaggle.

• Used Python libraries like Pandas, NumPy, and Scikit-learn for data preprocessing and modeling

• Performed feature engineering to improve model performance

• Evaluated model performance using metrics like RMSE and MAE

CNN stands for Convolutional Neural Networks, a type of deep learning algorithm commonly used for image recognition.

• CNNs are designed to automatically and adaptively learn spatial hierarchies of features from data.

• They consist of multiple layers of convolutional, pooling, and fully connected layers.

• CNNs have been widely used in computer vision tasks such as image classification, object detection, and facial recognition...read more

PCA is a dimensionality reduction technique used to transform high-dimensional data into a lower-dimensional space while preserving the most important information.

• PCA helps in identifying patterns in data by reducing the number of variables

• It finds the directions (principal components) along which the variance of the data is maximized

• PCA is commonly used in image processing, genetics, and finance

Central limit theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.

• Central limit theorem is a fundamental concept in statistics.

• It states that the sampling distribution of the sample mean will be approximately normally distributed, regardless of the shape of the population distribution.

• It is important for making inferences about population parame...read more

Random Forest is an ensemble learning algorithm that builds multiple decision trees and combines their predictions.

• Random Forest is a supervised learning algorithm used for classification and regression tasks.

• It creates a forest of decision trees during training, where each tree is built using a random subset of features and data points.

• The final prediction is made by aggregating the predictions of all the individual t...read more

Pruning is a technique used in machine learning to reduce the size of decision trees by removing unnecessary branches.

• Pruning helps prevent overfitting by simplifying the model

• There are two types of pruning: pre-pruning and post-pruning

• Pre-pruning involves setting a limit on the depth of the tree or the number of leaf nodes

• Post-pruning involves removing branches that do not improve the overall accuracy of the tree

• Examp...read more