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Data Analytics Projects: 9 Project Ideas for Your Portfolio

Edureka

As a data analytics professional, building a strong portfolio of projects is essential to showcase your skills and expertise to potential employers. This article will discuss nine data analytics project ideas for your portfolio. What is the Role of Data Analytics? Lest discuss about data analytics projects ideas in next section.

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50 ML Projects To Strengthen Your Portfolio and Get You Hired

ProjectPro

Each project explores new machine learning algorithms, datasets, and business problems. The dataset contains three weeks of activity data on each driver like login time, number of hours active each day, date, and driver details like driver gender, age, id, number of kids, etc. All the activities were tracked and video recorded.

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Top 22 Data Science Applications That You Should Know

Knowledge Hut

Medical Image Analysis Data science applications in healthcare or Medical science have several uses. Analyzing medical images is one of them. With more datasets and photos, clinicians will soon be able to diagnose patients more accurately with the help of machine learning.

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Top 15 Power BI Project Ideas

Knowledge Hut

No matter if you're just a beginner, intermediate, or advanced Power BI user, you can build up your portfolio by doing these projects. Additionally, showcasing these projects in your portfolio can demonstrate your ability to deliver actionable insights and drive data-informed decision-making for potential employers or clients.

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Veracity in Big Data: Why Accuracy Matters

Knowledge Hut

Big Data is the term used to describe extraordinarily massive and complicated datasets that are difficult to manage, handle, or analyze using conventional data processing methods. Outliers or Anomalies: Outliers are data points that significantly deviate from the normal pattern or distribution of the dataset. What is Big Data?

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10 Practical Generative AI Examples to be More Productive

Edureka

Getting Trained on Data: To perform any task, first, the generative AI models need to be trained on massive datasets of existing content. Gen AI models can give biased results as they are trained on massive datasets. If the dataset has any biases, then it will influence the outputs.

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How Financial Services and Insurance Streamline AI Initiatives with a Hybrid Data Platform

Cloudera

Under the terms of the AI Act, “high-risk” AI systems require a compulsory self-assessment by providers, with certain critical applications (like AI used in medical devices) also subject to review under existing EU regulations. Practice real-time risk management.