Hashwanth Gogineni

Data Science Skills

Artificial Intelligence	Statistical Modeling	Text Analytics
Big Data	Digital Analytics	Visualization
Python	R	Tableau

Domain Skills

Retail

Mushroom Classification

Category: Domain Usecases

Sub-Category: Agriculture

Use-case Type: Structured Data Predictions

Tags: agriculture,edible,healthy,machine learning,mushroom,mushroom classification,plant,poisonous,poisonous mushroom,random forest,rf,toxic

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Note: Certain Model Inferences can take long time for the first run (Warmup) and would get faster with the subsequent inferences. We thank you for your patience.

Use Case Summary

Mushroom poisonings can occur because of forager misidentification of a poisonous species as edible, although many cases are intentional ingestions. The project can identify 'Toxic mushrooms' and 'Edible mushrooms' to prevent humans from consuming them and falling sick. Likewise, organizations can use the project to weed out 'Poisonous Mushrooms' during production or harvesting. The dataset includes hypothetical samples corresponding to 23 gilled mushrooms in the Agaricus and Lepiota Family Mushroom drawn from The Audubon Society Field Guide to North American Mushrooms (1981). The "Accuracy_score" metric has been used to measure that model's performance.