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Startup Profit Prediction
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Finacial Domain/Indian Startup Funding analysis/Startup Profit Prediction/50_Startups.csv
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R&D Spend,Administration,Marketing Spend,State,Profit | ||
165349.2,136897.8,471784.1,New York,192261.83 | ||
162597.7,151377.59,443898.53,California,191792.06 | ||
153441.51,101145.55,407934.54,Florida,191050.39 | ||
144372.41,118671.85,383199.62,New York,182901.99 | ||
142107.34,91391.77,366168.42,Florida,166187.94 | ||
131876.9,99814.71,362861.36,New York,156991.12 | ||
134615.46,147198.87,127716.82,California,156122.51 | ||
130298.13,145530.06,323876.68,Florida,155752.6 | ||
120542.52,148718.95,311613.29,New York,152211.77 | ||
123334.88,108679.17,304981.62,California,149759.96 | ||
101913.08,110594.11,229160.95,Florida,146121.95 | ||
100671.96,91790.61,249744.55,California,144259.4 | ||
93863.75,127320.38,249839.44,Florida,141585.52 | ||
91992.39,135495.07,252664.93,California,134307.35 | ||
119943.24,156547.42,256512.92,Florida,132602.65 | ||
114523.61,122616.84,261776.23,New York,129917.04 | ||
78013.11,121597.55,264346.06,California,126992.93 | ||
94657.16,145077.58,282574.31,New York,125370.37 | ||
91749.16,114175.79,294919.57,Florida,124266.9 | ||
86419.7,153514.11,0,New York,122776.86 | ||
76253.86,113867.3,298664.47,California,118474.03 | ||
78389.47,153773.43,299737.29,New York,111313.02 | ||
73994.56,122782.75,303319.26,Florida,110352.25 | ||
67532.53,105751.03,304768.73,Florida,108733.99 | ||
77044.01,99281.34,140574.81,New York,108552.04 | ||
64664.71,139553.16,137962.62,California,107404.34 | ||
75328.87,144135.98,134050.07,Florida,105733.54 | ||
72107.6,127864.55,353183.81,New York,105008.31 | ||
66051.52,182645.56,118148.2,Florida,103282.38 | ||
65605.48,153032.06,107138.38,New York,101004.64 | ||
61994.48,115641.28,91131.24,Florida,99937.59 | ||
61136.38,152701.92,88218.23,New York,97483.56 | ||
63408.86,129219.61,46085.25,California,97427.84 | ||
55493.95,103057.49,214634.81,Florida,96778.92 | ||
46426.07,157693.92,210797.67,California,96712.8 | ||
46014.02,85047.44,205517.64,New York,96479.51 | ||
28663.76,127056.21,201126.82,Florida,90708.19 | ||
44069.95,51283.14,197029.42,California,89949.14 | ||
20229.59,65947.93,185265.1,New York,81229.06 | ||
38558.51,82982.09,174999.3,California,81005.76 | ||
28754.33,118546.05,172795.67,California,78239.91 | ||
27892.92,84710.77,164470.71,Florida,77798.83 | ||
23640.93,96189.63,148001.11,California,71498.49 | ||
15505.73,127382.3,35534.17,New York,69758.98 | ||
22177.74,154806.14,28334.72,California,65200.33 | ||
1000.23,124153.04,1903.93,New York,64926.08 | ||
1315.46,115816.21,297114.46,Florida,49490.75 | ||
0,135426.92,0,California,42559.73 | ||
542.05,51743.15,0,New York,35673.41 | ||
0,116983.8,45173.06,California,14681.4 |
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...cial Domain/Indian Startup Funding analysis/Startup Profit Prediction/README.md
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## **Startup Profit Prediction** | ||
**GOAL** | ||
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The goal of this project is to analyse and predict profit of a startup from features as 'R&D Spend', 'Administration', 'Marketing Spend', 'State' etc. | ||
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**DATASET** | ||
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Dataset can be downloaded from https://www.kaggle.com/sonalisingh1411/startup50 | ||
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**WHAT I HAD DONE** | ||
- Step 1: Data Exploration | ||
- Step 2: Data Preparation | ||
- Step 3: Data Training | ||
- Step 4: Model Creation | ||
- Step 5: Performance Check | ||
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**MODELS USED** | ||
- Linear Regression | ||
- Lasso Regression | ||
- Ridge Regression | ||
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**LIBRARIES NEEDED** | ||
- pandas | ||
- numpy | ||
- sklearn (For data training, importing models and performance check) | ||
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**Accuracy of different models used** | ||
- By using Linear Regression model | ||
```python | ||
Accuracy achieved : 94.87 | ||
``` | ||
- By using Lasso Regression model | ||
```python | ||
Accuracy achieved : 94.87 | ||
``` | ||
- By using Ridge Regression model | ||
```python | ||
Accuracy achieved : 94.87 | ||
``` | ||
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**CONCLUSION** | ||
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* All 3 regression algorithms used in this project are equally efficient for the given dataset. | ||
* RMSE for Ridge Regression is least |
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