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Description : Complete analysis of How Random Forest algorithm is implemented in Python and machine learning with real time use case of House price prediction using a complete iynb analysis file
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+ Create account on https://www.kaggle.com/ and report link to your profile page on Kaggle here. (1 hour)
+ Find 10 datasets that have at least more than 100 rows and 5 columns and report the links h…
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### Deep Learning Simplified Repository (Proposing new issue)
:red_circle: **Project Title** : Real Estate Price Prediction
:red_circle: **Aim** : Building an ML model to predict real estate price…
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The datapackage-pipeline cannot download and process the source.
## Acceptance criteria
* [ ] datapackage is processed after `data push-flow`
## Analysis
source link: https://www.nationwide.…
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This is an interesting report discussing an everyday issue: house buying. I really like the topic as this could be helpful to a lot of people. This report used data of house pricing and related featur…
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- Describe the goal of the project.
To describe how house prices changes from a set of factors. Then to identify the most affordable house given a set of conditions.
- Describe the data used o…
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It is a machine learning model which predicts the house price in Bangalore.
This model is trained using a dataset that contains information about 13321 houses. However, this dataset has a lot of miss…
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# App review
### group1
1. information of value or interesting
(1) include a lot of information of a neighborhood that one may be interested in:
price, transportation (subway), safety (crime), e…
RxBai updated
6 years ago
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Does the 1st or the 2nd file contain 15 samples?
I feel that question 2 can be answered based on the output of question 1. What are the difference between time series plot in question 1 and line char…