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This event provides a unique opportunity to contribute to the global data economy, with applications spanning healthcare, government, and more. Ocean Protocol, known for its robust toolkit enabling general-purpose access to share, monetize, and access data while preserving privacy, serves as the backbone tech stack for this event.
Learning Objectives Recap: Paradigms in Data Science: We explored the two main paradigms in data science: descriptive analytics (understanding what happened in the past) and predictiveanalytics (using models to forecast future outcomes). It learns from historical data to make predictions about future events.
Using the right data analytics techniques can help in extracting meaningful insight, and using the same to formulate strategies. The analytics techniques like descriptive analytics, predictiveanalytics, diagnostic analytics and others find application in diverse industries, including retail, healthcare, finance, and marketing.
2022 & 2023 data challenges tested different time durations between 7–30 days. It has been determined that initiatives and hypothesistesting that require longer than 20 days will be tagged and executed as something other than a data challenge (data science competition). continue to roll out regularly.
Areas like automation, data processing, and predictiveanalytics were potential fields to explore for solutions. [link] Objectives & Outcomes: Before : This was for individuals or teams to create their own business proposal that has real-life applicability.
Key Objectives of Statistical Modeling Prediction : One of the primary goals of Statistical Modeling is to predict future outcomes based on historical data. This is especially useful in finance and weather forecasting, where predictions guide decision-making. They are essential in scientific research for concluding limited data.
Different approaches help organisations make sense of raw data, from simply summarising past events to predicting future outcomes. This section will explore six common types of Data Analysis: Descriptive, Exploratory, Inferential, Predictive, Diagnostic, and Prescriptive.
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