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Steph Curry Shot Analysis Objective Analyze Steph Curry’s historical shot data using Python. Learn to load, clean, visualize data, and explain AI-related insights. You will need to create, explain each step briefly, and interpret key results. Stephen Curry, star player for the Golden State Warriors, is known for his revolutionary three-point shooting. Analyzing his shot data shows patterns in his performance — useful for AI models predicting shot success. This assignment uses his 2009–2019 shot data. Dataset Overview Each row = 1 shot attempt, including: Game info (date, period) Shot details (type, location) Outcome (made/missed) Tasks: Using data from here: https://www.murach.com/python_analysis/shots.json For each specified code cell, run the code and explain what the code does and what the output means.  Focus on understanding and explaining. In addition answer  the following Questions : Predictive Modeling: How could you use this dataset to predict if a shot will be made? Feature Improvement: What extra data would make predictions more accurate? Limitations: What challenges arise when predicting shots from past data alone? Clearly label each section: Task number + explanation

Steph Curry Shot Analysis Objective Analyze Steph Curry’s historical shot data using Python. Learn to load, clean, visualize data, and explain AI-related insights. You will need to create, explain each step briefly, and interpret key results. Stephen Curry, star player for the Golden State Warriors, is known for his revolutionary three-point shooting. Analyzing his shot data shows patterns in his performance — useful for AI models predicting shot success. This assignment uses his 2009–2019 shot data. Dataset Overview Each row = 1 shot attempt, including: Game info (date, period) Shot details (type, location) Outcome (made/missed) Tasks: Using data from here: https://www.murach.com/python_analysis/shots.json For each specified code cell, run the code and explain what the code does and what the output means.  Focus on understanding and explaining. In addition answer  the following Questions : Predictive Modeling: How could you use this dataset to predict if a shot will be made? Feature Improvement: What extra data would make predictions more accurate? Limitations: What challenges arise when predicting shots from past data alone? Clearly label each section: Task number + explanation

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Steph Curry Shot Analysis

Objective Analyze Steph Curry’s historical shot data using Python. Learn to load, clean, visualize data, and explain AI-related insights. You will need to create, explain each step briefly, and interpret key results.

Stephen Curry, star player for the Golden State Warriors, is known for his revolutionary three-point shooting. Analyzing his shot data shows patterns in his performance — useful for AI models predicting shot success. This assignment uses his 2009–2019 shot data.

Dataset Overview Each row = 1 shot attempt, including:

  • Game info (date, period)

  • Shot details (type, location)

  • Outcome (made/missed)

Tasks:

Using data from here: https://www.murach.com/python_analysis/shots.json

For each specified code cell, run the code and explain what the code does and what the output means.  Focus on understanding and explaining.

In addition answer  the following Questions :

  • Predictive Modeling: How could you use this dataset to predict if a shot will be made?

  • Feature Improvement: What extra data would make predictions more accurate?

  • Limitations: What challenges arise when predicting shots from past data alone?

  • Clearly label each section: Task number + explanation

 

 

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