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I approach building a ML model by understanding the problem, collecting data, preprocessing data, selecting a model, training the model, evaluating the model, and deploying it.
Understand the problem and define the objective
Collect and preprocess data
Select an appropriate model based on the problem
Train the model using the data
Evaluate the model's performance using metrics like accuracy, precision, recall, etc.
Deploy th...
Top trending discussions
PCA is a dimensionality reduction technique, decision tree is a classification algorithm, and computer vision is a field of study focused on enabling computers to interpret and understand visual information.
PCA is used to reduce the number of variables in a dataset while retaining the most important information.
Decision trees are used to classify data based on a set of rules and conditions.
Computer vision involves usin...
I applied via Job Portal and was interviewed in Jan 2021. There were 3 interview rounds.
A good data scientist needs strong analytical skills, programming expertise, and effective communication abilities.
Analytical Skills: Ability to interpret complex data sets and derive actionable insights. For example, using statistical methods to identify trends.
Programming Expertise: Proficiency in languages like Python or R for data manipulation and analysis. For instance, using Python libraries like Pandas and NumPy...
I applied via Referral and was interviewed before Jul 2023. There were 2 interview rounds.
If else conditions, data merging, datetime conversions, EDA on a sample data set, duplicates removal and missing value imputation
To target customers for a kids account, focus on features like parental controls, educational content, and interactive games.
Implement parental controls to assure parents of child safety online.
Include educational content to attract parents looking for learning opportunities.
Incorporate interactive games to engage children and make the account more appealing.
Offer rewards or incentives for completing educational activi...
Choosing the right model depends on data characteristics, problem complexity, and performance metrics.
Model performance: Some models may outperform others based on metrics like accuracy, precision, or recall. For example, Random Forest may perform better than Logistic Regression on complex datasets.
Data characteristics: The nature of the data (e.g., linear vs. non-linear relationships) influences model choice. For inst...
I appeared for an interview in Oct 2024, where I was asked the following questions.
Bias refers to error due to overly simplistic assumptions, while variance refers to error due to excessive complexity in the model.
Bias is the error introduced by approximating a real-world problem with a simplified model. Example: A linear model for a non-linear relationship.
Variance is the error introduced by the model's sensitivity to small fluctuations in the training data. Example: A complex model that fits noise.
...
I applied via Campus Placement and was interviewed in Apr 2023. There were 3 interview rounds.
Java script, angular js, node questions
I applied via Naukri.com and was interviewed before Apr 2022. There were 3 interview rounds.
DS related Case study and discussion
Python code example test where they will ask basic python or sql questions.
based on 1 interview experience
Difficulty level
TCS
HDFC Bank
ICICI Bank
Genpact