JIJI KJ

Adult income census using Machine Learning, 

 Objective: Analysis of adult income census data using machine learning techniques to predict income levels based on demographic features. Leveraged a dataset encompassing variables such as age, gender, occupation, and education to develop predictive models.

, Conducted extensive data preprocessing, including handling missing values, feature scaling, and encoding categorical variables

. Communicated findings and insights effectively through data visualization techniques, including histograms, box plots, and correlation matrices

Methodology used: Python, pandas, NumPy, scikit-learn for data preprocessing and modeling. Matplotlib, Seaborn for data visualization., Python, pandas, NumPy, scikit-learn for data preprocessing and modeling. Matplotlib, Seaborn for data visualization.,

Outcome :  Successfully developed a predictive model with an accuracy of 84 %providing valuable insights into the factors influencing adult income levels. The project demonstrated proficiency in data analysis, machine learning, and problem-solving skills