Anik Kumar

• Developed some Tableau dashboards for different types of data, allowing for more informed decision-making and improved outcomes.
• Developed interactive visualizations and reports in Tableau to monitor key performance indicators and track progress toward business goals.
• Utilized data blending and calculated fields to combine and transform data from various sources for comprehensive analysis.

• Developed a machine learning model using Python to predict the likelihood of heart failure in patients with an accuracy of 91%
• Utilized the Heart Failure Clinical Records dataset from Kaggle to train and test the model.
• Employed various data preprocessing techniques to handle missing values and categorical variables.
• Utilized several classification algorithms to compare their performance and selected the best-performing one.
• Optimized the model using hyperparameter tuning… আরও দেখান

• Developed a machine learning model using Python to predict the likelihood of heart failure in patients with an accuracy of 91%
• Utilized the Heart Failure Clinical Records dataset from Kaggle to train and test the model.
• Employed various data preprocessing techniques to handle missing values and categorical variables.
• Utilized several classification algorithms to compare their performance and selected the best-performing one.
• Optimized the model using hyperparameter tuning to improve its accuracy.
• Validated the model using various evaluation metrics such as confusion matrix and classification report. কম করে দেখান

• Developed an advanced pipeline for predicting house prices using various regression models, such as linear regression, random forest, and xgboost, and achieved an RMSE of 0.12764
• Implemented K-fold cross-validation for model evaluation and hyperparameter tuning.
• Utilised feature engineering and hyperparameter tuning to optimize the model performance.
• Utilized various Python libraries such as pandas, numpy, scikit-learn, and xgboost for data cleaning, exploration, and modeling.

• Developed a machine learning model using the Breast Cancer Wisconsin Diagnostic dataset to classify breast cancer tumors with an accuracy of 98%.
• Utilized various classification algorithms including Logistic Regression, Random Forest, and KNN to determine the most effective method for predicting breast cancer.
• Preprocessed and cleaned data to improve model performance and reduce the number of false positives and false negatives.
• Analyzed the importance of different features in… আরও দেখান

• Developed a machine learning model using the Breast Cancer Wisconsin Diagnostic dataset to classify breast cancer tumors with an accuracy of 98%.
• Utilized various classification algorithms including Logistic Regression, Random Forest, and KNN to determine the most effective method for predicting breast cancer.
• Preprocessed and cleaned data to improve model performance and reduce the number of false positives and false negatives.
• Analyzed the importance of different features in the dataset and their impact on the accuracy of the model. কম করে দেখান