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Blackstraw AI
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I applied via Company Website and was interviewed in May 2024. There were 2 interview rounds.
Data leakage occurs when information from outside the training dataset is used to create a model, leading to unrealistic performance.
Occurs when information that would not be available in a real-world scenario is used in the model training process
Can result in overly optimistic performance metrics for the model
Examples include using future data, target leakage, and data preprocessing errors
Encoder Decoder is a neural network architecture used for sequence-to-sequence tasks. Transformer model is a type of neural network architecture that relies entirely on self-attention mechanisms.
Encoder Decoder is commonly used in machine translation tasks where the input sequence is encoded into a fixed-length vector representation by the encoder and then decoded into the target sequence by the decoder.
Transformer mod...
Deep learning models include CNN, RNN, LSTM, GAN, and Transformer.
Convolutional Neural Networks (CNN) - used for image recognition tasks
Recurrent Neural Networks (RNN) - used for sequential data like time series
Long Short-Term Memory (LSTM) - a type of RNN with memory cells
Generative Adversarial Networks (GAN) - used for generating new data samples
Transformer - used for natural language processing tasks
Regularization is a technique used in machine learning to prevent overfitting by adding a penalty term to the model's loss function.
Regularization helps to reduce the complexity of the model by penalizing large coefficients.
It adds a penalty term to the loss function, which discourages the model from fitting the training data too closely.
Common types of regularization include L1 (Lasso) and L2 (Ridge) regularization.
Re...
Model quantization is the process of reducing the precision of the weights and activations of a neural network model to improve efficiency.
Reduces memory usage and speeds up inference by using fewer bits to represent numbers
Can be applied to both weights and activations in a neural network model
Examples include converting 32-bit floating point numbers to 8-bit integers
I applied via Job Portal and was interviewed before Apr 2023. There were 2 interview rounds.
ML algorithm selection is based on data characteristics, problem type, and desired outcomes.
Understand the problem type (classification, regression, clustering, etc.)
Consider the size and quality of the data
Evaluate the complexity of the model and interpretability requirements
Choose algorithms based on their strengths and weaknesses for the specific task
Experiment with multiple algorithms and compare their performance
F...
To optimize a ML model, one can tune hyperparameters, feature engineering, cross-validation, ensemble methods, and regularization techniques.
Tune hyperparameters using techniques like grid search or random search
Perform feature engineering to create new features or select relevant features
Utilize cross-validation to evaluate model performance and prevent overfitting
Explore ensemble methods like bagging and boosting to ...
I applied via Naukri.com and was interviewed before Mar 2023. There were 3 interview rounds.
Top trending discussions
My friends think of me as reliable, supportive, and always up for a good time.
Reliable - always there when they need help or support
Supportive - willing to listen and offer advice
Fun-loving - enjoys socializing and trying new things
posted on 11 Dec 2024
I applied via LinkedIn and was interviewed in Nov 2024. There were 2 interview rounds.
There are 10 multiple-choice questions (MCQs) on Python, 20 MCQs on machine learning (ML), and 10 questions on deep learning (DL).
I applied via Naukri.com and was interviewed in Apr 2022. There were 3 interview rounds.
I applied via Campus Placement and was interviewed in Jul 2022. There were 4 interview rounds.
Medium level of question are there in this section
Basic level of question are there in this section
Joints are connections between bones that allow movement and provide support to the body.
Joints are found throughout the body, such as the knee, elbow, and shoulder.
They are made up of bones, cartilage, ligaments, and synovial fluid.
Joints enable various types of movements, including flexion, extension, rotation, and abduction.
Different types of joints include hinge joints, ball-and-socket joints, and pivot joints.
Join...
I'm not sure how joints relate to data science, but my hobby is playing guitar.
Joints can refer to the connection between two bones in the body or the way two things are connected or joined together.
Playing guitar is a hobby that helps me relax and unwind after a long day of working with data.
While seemingly unrelated to data science, playing an instrument can actually improve cognitive function and creativity, which c
I applied via Naukri.com and was interviewed in Sep 2021. There were 4 interview rounds.
I applied via LinkedIn
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