Data ScienceData Collection and Preprocessing:
- Gather and clean data from various sources (e.g., databases, APIs, web scraping).
- Perform data validation and ensure data quality.
- Transform and prepare data for analysis and modeling.
Data Analysis and Modeling:
- Conduct exploratory data analysis (EDA) to identify patterns and trends.
- Develop and implement machine learning models (e.g., regression, classification, clustering).
- Evaluate model performance and optimize for accuracy and efficiency.
- Apply statistical techniques and algorithms to solve business problems.
Data Visualization and Reporting:
- Create compelling visualizations to communicate insights to stakeholders.
- Develop dashboards and reports to track key performance indicators (KPIs).
- Present findings to technical and non-technical audiences.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Data ScienceMachine Learning (ML)
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Full Stack Developer - Averlon