Saswat Seth

Data collection and preprocessing.

Handling missing values and inconsistencies.

Data transformation and normalization.

Merging, filtering, and restructuring datasets.

Ensuring data quality and integrity.

Designing clear and impactful charts and graphs.

Developing interactive dashboards and reports.

Enhancing data storytelling through visual insights.

Selecting the right visualization techniques for data.

Communicating complex data trends effectively.

Summarizing and understanding data distributions.

Identifying patterns, trends, and correlations.

Detecting outliers and anomalies.

Visualizing relationships between variables.

Guiding feature selection and data preprocessing.

Performing hypothesis testing and inference.

Identifying trends and relationships in data.

Building and evaluating regression models.

Measuring statistical significance and confidence intervals.

Making data-driven predictions and recommendations.

Creating new features from raw data.

Selecting the most relevant features for modeling.

Transforming and scaling data for better model performance.

Encoding categorical variables effectively.

Reducing dimensionality to improve efficiency.

Selecting appropriate machine learning algorithms.

Training and evaluating predictive models.

Tuning hyperparameters for optimal performance.

Validating models using cross-validation techniques.

Deploying models for real-world applications.