Python Data Science Jobs & Interviews
❔ Question 75: #MachineLearning
What is the primary goal of using cross-validation in model evaluation?
What is the primary goal of using cross-validation in model evaluation?
❤️ Cross-validation is a model evaluation technique designed to assess how well a machine learning model generalizes to unseen data.
✅ Cross-validation works by partitioning the dataset into multiple subsets, or folds. The model is trained on some of these folds and validated on the remaining ones, rotating the validation set across all folds. This approach provides a more comprehensive evaluation by ensuring that every data point is used for both training and validation. It helps to assess the model’s robustness and performance across different subsets of the data, reducing the risk of overfitting to any particular split and offering a more accurate estimate of how the model will perform on new, unseen data.
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✅ Cross-validation works by partitioning the dataset into multiple subsets, or folds. The model is trained on some of these folds and validated on the remaining ones, rotating the validation set across all folds. This approach provides a more comprehensive evaluation by ensuring that every data point is used for both training and validation. It helps to assess the model’s robustness and performance across different subsets of the data, reducing the risk of overfitting to any particular split and offering a more accurate estimate of how the model will perform on new, unseen data.
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Python Data Science Jobs & Interviews
Your go-to hub for Python and Data Science—featuring questions, answers, quizzes, and interview tips to sharpen your skills and boost your career in the data-driven world.
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Question: What is the output of print tinylist * 2 if tinylist = [123, 'john']?
Anonymous Quiz
57%
[123, 'john', 123, 'john']
23%
[246, 'johnjohn']
14%
[123, 123, 'john', 'john']
6%
[246, 'john']
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Which of the following is NOT a type of machine learning?
Anonymous Quiz
3%
Supervised leaning
8%
Unsupervised learning
71%
Predictive learning
18%
Reinforcement learning
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For each role except for data analyst where programming is not explicitly required, it’s important to learn a programming language like Python. Knowing SQL is equally as important for all roles.
Data science is the first role that embraces machine learning, and as you’re headging towards AI, you’ll see its subsets like deep learning, reinforcement learning, as well as computer vision and NLP.
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Data science is the first role that embraces machine learning, and as you’re headging towards AI, you’ll see its subsets like deep learning, reinforcement learning, as well as computer vision and NLP.
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What is the most important step in the data science process?
Anonymous Quiz
29%
Data collection
39%
Data cleaning
26%
Data analysis
6%
Data visualization
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Python Data Science Jobs & Interviews
What is the most important step in the data science process?
Explanation :
While all steps are crucial, clean and accurate data is the foundation for any successful data science project!
While all steps are crucial, clean and accurate data is the foundation for any successful data science project!
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What type of project do you enjoy working on the most?
1. Personal projects
2. Open-source contributions
3. Freelance work
4. Corporate projects
5. Academic projects
If any other, add in comments 👇👇
1. Personal projects
2. Open-source contributions
3. Freelance work
4. Corporate projects
5. Academic projects
If any other, add in comments 👇👇
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Which of the following is a common programming language used in data science?
Anonymous Quiz
67%
Python
6%
R
3%
Java
24%
Both A & B
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import array as arr
My_Array=arr.array('i',[1,2,3,4,5])
My_Array[::-1]
Output: array('i', [5, 4, 3, 2, 1])
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1. In the outer_func function, x is created with the value 2.
2. Next, the inner_func function is declared, it does not remember the value of x or y immediately, but will receive it only when it is used.
3. x becomes equal to x + 2, i.e. 4, y is declared with the value 2
4. the return block (x(4) + y(2) = 6) is executed.
5. Despite declaring the value y = 3, the inner_func function will be called only after returning the value y = 2. Therefore, the output will be 6.
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