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Random forest is an ensemble learning method using multiple decision trees to improve accuracy and reduce overfitting.
Random forest uses multiple decision trees to make predictions.
Decision tree is a single tree structure used for classification and regression.
Random forest reduces overfitting by averaging the predictions of multiple trees.
Decision tree can be prone to overfitting if not pruned properly.
Random forest i...
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Overfitting in decision trees occurs when the model learns noise in the training data rather than the underlying pattern.
Overfitting happens when the decision tree is too complex and captures noise in the training data.
It leads to poor generalization on unseen data, as the model is too specific to the training set.
To prevent overfitting, techniques like pruning, setting a minimum number of samples per leaf, or using en
Bagging is a machine learning ensemble technique where multiple models are trained on different subsets of the training data and their predictions are combined.
Bagging stands for Bootstrap Aggregating.
It helps reduce overfitting by combining the predictions of multiple models.
Random Forest is a popular algorithm that uses bagging by training multiple decision trees on random subsets of the data.
A neuron is a basic unit of a neural network that receives input, processes it, and produces an output.
Neurons are inspired by biological neurons in the human brain.
They receive input signals, apply weights to them, sum them up, and pass the result through an activation function.
Neurons are organized in layers in a neural network, with each layer performing specific tasks.
In deep learning, multiple layers of neurons ar...
I applied via Referral and was interviewed in Nov 2022. There were 3 interview rounds.
Hypothesis testing is a statistical method to test a claim about a population parameter. Type 1 error is rejecting a true null hypothesis, and type 2 error is failing to reject a false null hypothesis.
Hypothesis testing involves formulating a null hypothesis and an alternative hypothesis.
Type 1 error occurs when we reject a null hypothesis that is actually true.
Type 2 error occurs when we fail to reject a null hypothes...
Basic quants,lrdi and coding round
I applied via Campus Placement and was interviewed in Oct 2022. There were 4 interview rounds.
SQL and quant, logical questions were asked.
I applied via campus placement at Muffakhamjah College of Engineering and Technology, Hyderabad and was interviewed before May 2022. There were 5 interview rounds.
It was a hybrid type of test it consisted of 3 sections
1. Aptitude
2. 2 DSA questions only the algorithm was to be written on the paper
3. 5 SQL queries (Intermediate level)
To find the minimum element in a stack in O(1) complexity, we can use an auxiliary stack.
Create an auxiliary stack to keep track of the minimum element.
Push the first element of the main stack onto the auxiliary stack.
For each subsequent element, compare it with the top element of the auxiliary stack.
If it is smaller, push it onto the auxiliary stack.
To get the minimum element, simply return the top element of the auxi...
Basic test with Data Structures, algorithms, SQL questions
I applied via campus placement at University Business School (UBS), Chandigarh and was interviewed before Aug 2022. There were 4 interview rounds.
It consist of questions related to aptitude, basic computer science, statistics.
Join is a SQL operation used to combine rows from two or more tables based on a related column between them.
Types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN
INNER JOIN returns rows when there is at least one match in both tables
LEFT JOIN returns all rows from the left table and the matched rows from the right table
RIGHT JOIN returns all rows from the right table and the matched rows from the left ...
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