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Implementation of ML concepts in projects involves identifying suitable algorithms, collecting and preprocessing data, training models, and evaluating performance.
Identify the problem to be solved and determine if ML is the appropriate solution
Collect and preprocess data to ensure it is clean and relevant for training
Select suitable algorithms based on the problem and data characteristics
Train the models using the data...
Data integration & pipeline involves combining data from multiple sources and processing it to make it usable for analysis.
Data integration is the process of combining data from different sources into a single, unified view.
Data pipeline refers to the series of steps that data goes through from collection to analysis.
Data integration ensures that data is clean, consistent, and accurate before being processed in the pip...
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I applied via Approached by Company and was interviewed in Nov 2024. There were 3 interview rounds.
3 question were asked in 90 min time
Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.
Precision is calculated as TP / (TP + FP), where TP is true positives and FP is false positives.
It measures the accuracy of positive predictions made by the model.
A high precision indicates that the model is good at predicting positive cases without many false positives.
For example, in a binary classificatio...
A large language model is a type of artificial intelligence model that is capable of understanding and generating human language at a large scale.
Large language models use deep learning techniques to process and generate text.
Examples include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers).
Adam optimizer is an extension to the Gradient Descent optimizer with adaptive learning rates and momentum.
Adam optimizer combines the benefits of both AdaGrad and RMSProp optimizers.
Adam optimizer uses adaptive learning rates for each parameter.
Gradient Descent optimizer has a fixed learning rate for all parameters.
Adam optimizer includes momentum to speed up convergence.
Gradient Descent optimizer updates parameters b...
Use ReLU for hidden layers in deep neural networks, avoid for output layers.
ReLU is commonly used in hidden layers to introduce non-linearity and speed up convergence.
Avoid using ReLU in output layers for regression tasks as it can lead to vanishing gradients.
Consider using Leaky ReLU or Sigmoid for output layers depending on the task.
ReLU is computationally efficient and helps in preventing the vanishing gradient prob...
I applied via Naukri.com and was interviewed in Jan 2024. There was 1 interview round.
I applied via Company Website and was interviewed in Sep 2023. There were 4 interview rounds.
Sql and python questions were there with basic logic check
Python code with function
Define a function using 'def' keyword
Include parameters inside parentheses
Use 'return' statement to return a value from the function
I applied via campus placement at Indian Institute of Technology (IIT), Kharagpur and was interviewed before Jul 2023. There were 3 interview rounds.
Mostly data related question and two coding questions which we had to do in python only
Attention in data science refers to the mechanism that allows models to focus on specific parts of the input data.
Attention mechanisms help models to weigh the importance of different input features.
They are commonly used in natural language processing tasks such as machine translation and text summarization.
Attention can improve the performance of models by allowing them to selectively focus on relevant information.
Ex...
Efficiency of LLMs can be judged based on various factors such as accuracy, speed, resource consumption, and interpretability.
Evaluate accuracy by comparing LLM predictions with ground truth labels
Assess speed by measuring the time taken for LLM to process data
Analyze resource consumption in terms of memory and computational power usage
Consider interpretability by examining how easily LLM decisions can be understood
Use...
I applied via Company Website and was interviewed in Dec 2023. There were 3 interview rounds.
Standard question from sql and python in hackerrank
Reverse a linked list by changing the direction of pointers
Start with three pointers: current, previous, and next
Iterate through the linked list, updating pointers to reverse the direction
Return the new head of the reversed linked list
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