Order bagging and Boosting assessment
How to select k in KNN algorithm?
Q13: How to implement K means in Python?
Q14: How can accuracy of any model be calculated?
Q15: Explain regression metrics.
Q16: Explain how we can print a decision tree or see the rules of the decision tree?
Q17: What is the use of boosting techniques?
Q18: Explain some of the advantages and disadvantages of boosting techniques?
Q19: What is AdaBoost?
Q20: Explain Gradient boosting?
Q21: Explain XGBoost?
Q22: Explain the differences/similarities between bagging and Boosting?
Q23: Write a small snippet to perform operation with neural networks using tensorflow and keras?
1. Matplotlib Samples to Remember
Q1: Explain how to draw bar plot.
Q2: How to draw histogram?
Q3: How to draw line chart?
Q4: Draw Pie chart.
Q5: How to get the equation of the line printed line plot?
Q6: Draw scatter plot.
1. Statistics with Excel Sheet
Q1: Does Excel has any support for statistics?
Q2: Find correlation using Excel.
Q3: How to get Histogram in excel?
Q4: Explain how to get Descriptive Statistics using Excel.
Q5: Explain how to perform Anova in excel?
Q6: Explain how to perform Rank and Percentile in excel.
CHAPTER 1
Data Science Basic Questions and Terms
Note: [Q: Question Number and Ans: Answer]
Q1: Explain the steps involved in data science?
Ans: Following are the steps involved:
Get data from various data sources available.
Generate research question from data.
Identify variables present in data. Also, identify important variables or variables to be analyzed as such.
Generate hypothesis.
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