Dallas Technologies Interview Questions, Process, and Tips

Q1. Define Data Science & analytics?.
Ans. 
Data Science is the field of study that uses scientific methods, algorithms, and systems to extract knowledge and insights from data.
• Data Science involves collecting, analyzing, and interpreting large amounts of data to make informed decisions.

• It combines statistics, machine learning, and computer science to uncover patterns and trends in data.

• Data Analytics focuses on analyzing data to draw conclusions and make recomm...read more
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Q2. What is neural network?
Ans. 
Neural network is a type of machine learning algorithm inspired by the human brain's neural network structure.
• Neural network consists of layers of interconnected nodes (neurons) that process information.

• It can be used for tasks like image recognition, natural language processing, and predictive analytics.

• Common types of neural networks include feedforward, convolutional, and recurrent neural networks.
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Q3. Define Regression and classification?
Ans. 
Regression predicts continuous outcomes, while classification predicts categorical outcomes.
• Regression is used to predict continuous values based on input features.

• Classification is used to predict categories or classes based on input features.

• Examples of regression include predicting house prices based on features like size and location.

• Examples of classification include predicting whether an email is spam or not base
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Python pandas through data analytics.
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Q1. What is interpreted language?
Ans. 
Interpreted language is executed line by line at runtime, without the need for compilation.
• Code is translated and executed on the fly

• Errors are found during runtime

• Examples: Python, JavaScript, Ruby
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Q2. Define perceptron?(Ann,Cnn and Rnn)
Ans. 
Perceptron is a type of artificial neuron used in machine learning for binary classification.
• Perceptron is the simplest form of neural network.

• It takes input values, applies weights, sums them up, and passes the result through an activation function.

• It is used for binary classification tasks, where it predicts whether an input belongs to one class or another.

• Examples include single-layer perceptrons and multi-layer per
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Python,r,c,c++,sql related test