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Graph based question, acyclic graph
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180 mins of online test with camera ON. Major topics include Excel, Aptitude, Python, Statistics and Case Study
Apriori method is a popular algorithm for frequent itemset mining in data mining.
Used for finding frequent itemsets in transactional databases
Based on the concept of association rule mining
Involves generating candidate itemsets and pruning based on support threshold
Example: If {milk, bread} is a frequent itemset, then {milk} and {bread} are also frequent
Train-test split is a method used to divide a dataset into training and testing sets for model evaluation in Scikit learn.
Split the dataset into two subsets: training set and testing set
Training set is used to train the model, while testing set is used to evaluate the model's performance
Common split ratios are 70-30 or 80-20 for training and testing sets
Example: X_train, X_test, y_train, y_test = train_test_split(X, y,
I applied via Naukri.com and was interviewed in May 2022. There were 3 interview rounds.
I applied via Approached by Company and was interviewed before Sep 2021. There were 3 interview rounds.
Explain dynamic programming with memoization
I applied via Campus Placement and was interviewed in Oct 2023. There was 1 interview round.
I applied via Job Portal and was interviewed in Dec 2022. There were 2 interview rounds.
Faster-RCNN and Yolo v3 are both object detection algorithms, but differ in their approach and performance.
Faster-RCNN uses a two-stage approach, first generating region proposals and then classifying them.
Yolo v3 uses a single-stage approach, directly predicting bounding boxes and class probabilities.
Faster-RCNN is generally more accurate but slower, while Yolo v3 is faster but less accurate.
Faster-RCNN is better suit...
RNN uses techniques like gradient clipping, weight initialization, and LSTM/GRU cells to handle exploding/vanishing gradients.
Gradient clipping limits the magnitude of gradients during backpropagation.
Weight initialization techniques like Xavier initialization help in preventing vanishing gradients.
LSTM/GRU cells have gating mechanisms that allow the network to selectively remember or forget information.
Batch normaliza...
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