Bosch Production Line Performance Data Science Project

In this data science project, we will predict internal failures of Bosch using thousands of measurements and tests made for each component along the assembly line.


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What will you learn

  • Understanding the problem statement

  • Importing the dataset and importing libraries

  • Performing basic EDA and checking for null values

  • Handling imbalanced and Noisy dataset

  • Imputing the null values filling them using appropriate method

  • Changing categorical variables into numerical vectors

  • Selecting the best evaluation metrics

  • Applying probabilistic model BernoulliNB for training

  • Applying ensemble model Random Forest Classifier for training

  • Applying ensemble model Extra Tree Classifier for training

  • Applying XGBoost Classifier for training

  • Defining parameters for applying GRID SEARCH CV

  • Using Cross Folds Validation to prevent overfitting

  • Selecting the best model

  • Using Correlation and Violin plot for selecting best features for the model

  • Training the final model with the best features selected and making the final predictions

  • Saving the predictions made in the form of CSV

Project Description

A good chocolate souffle is decadent, delicious, and delicate. But, it's a challenge to prepare. When you pull a disappointingly deflated dessert out of the oven, you instinctively retrace  your steps to identify at what point you went wrong. Bosch, one of the world's leading manufacturing companies, has an imperative to ensure that the recipes for the production of its advanced mechanical components are of the highest quality and safety standards. Part of doing so is closely monitoring its parts as they progress through the manufacturing processes.

Because Bosch records data at every step along its assembly lines, they have the ability to apply advanced analytics to improve these manufacturing processes. However, the intricacies of the data and complexities of the production line pose problems for current methods.

In this data science project, you will use production line dataset to predict internal failures using thousands of measurements and tests made for each component along the assembly line. This would enable Bosch to bring quality products at lower costs to the end user.

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Curriculum For This Mini Project

02h 33m
02h 15m