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👋 Hi, this is a Data scientist project !

🛢️ We wanted to predict the oil price with an existing database. We went through all the basic steps:
-Define the goal
-Collect and clean the data
-Construct hypothesis with data visualization
-Construct the models
-Present the results and adapt

💲💲 After this cycles, we tried to add more data, always in order to improve the efficiency of the tested models/

🤓 Tech stack

PythonPandas Matplotlib scikit-learn

Very fast summary !

🧹 1st step: Clean the Data

Data cleaning

Heat Map

Correlations

Distribution

Outliers


👀 2nd step: Data visualization

Year oil

Events



📐3rd step: Construct the models.

We chose Elastic Net, SVM, Random Forest and ANN.

📈 4th step: Present the results

Results