A<\/em> significant number of newcomers in data science<\/strong> tend to spend a huge amount of time to develop theoretical knowledge and earn certifications only. While theoretical knowledge is certainly required to become a good data science<\/strong> professional, recruiters don\u2019t put much emphasis on certifications only. Instead, they tend to evaluate the potential of a candidate by going through his\/her work.<\/p>\n

As a data science<\/strong> professional, you may have worked on lots of crucial problems, but if you fail to present them to the recruiters, getting a good job in the field may become even more difficult. And this is exactly where data science<\/strong> projects<\/strong> come to your rescue. They help you demonstrate your data science<\/strong> skills to prospective employers. Therefore, it\u2019s important to pick your data science<\/strong> projects<\/strong> carefully. The process of picking up data science projects<\/strong> can be overwhelming, especially when you\u2019re planning to mention them in your CV. In this post, we\u2019ve outlined five top data science projects<\/strong> to help you in your endeavor.<\/p>\n

1- Movie Recommendation Engine<\/strong><\/h3>\n

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This<\/em> is one of the most common data science<\/strong> projects for everyone in the field. Every successful data science<\/strong> professional has developed at least one recommendation engine in the entire career. Personalized recommendation engines are considered highly effective when it comes to demonstrating data science<\/strong> skills.<\/p>\n

Problem: To analyze the Movie Lens dataset in order to comprehend patterns and trends that will help the system to recommend new movies to users.<\/p>\n

2- Walmart Sales forecasting<\/strong><\/h3>\n

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Retail<\/em> is one of those industries where data science<\/strong> is being used extensively and thus, it\u2019s important to have worked on at least one project related to it. There\u2019re a plethora of tasks including inventory management, product placement, product bundling, customized offers etc are being handled efficiently utilizing different types of data science<\/strong> techniques.<\/p>\n

Problem: Predict the department-wise sales of the store.<\/p>\n

3- Text Mining<\/strong><\/h3>\n

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A<\/em> text mining project in your portfolio may dramatically improve your chances of being hired as a data science<\/strong> professional. It involves data mining and advanced analytics that can prove your skills as a professional. Text mining is heavily used in social media monitoring as it helps to obtain an overview of a broader public opinion on specific topics.<\/p>\n

Problem: Classify a set of documents according to specific labels.<\/p>\n

4- Urban Sound Classification<\/strong><\/h3>\n

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This<\/em> is one of those data science projects<\/strong> that will help you demonstrate skills in machine learning. This project is designed to getting you introduced to audio processing in the context of the usual classification scenario.<\/p>\n

Problem: Classify the kind of sound from an audio.<\/p>\n

5- Chicago Crime Analysis<\/strong><\/h3>\n

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Law<\/em> enforcement agencies take help of data science<\/strong> techniques to understand the actual reasons behind crimes and thus, to be able to prevent their repetitions. While the problem may seem easy, data management is the key here.<\/p>\n

Problem: Predict the type of crime.<\/p>\n

Parting Thoughts<\/em><\/strong><\/h3>\n

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If<\/em> you\u2019re a complete beginner in the data science<\/strong> field, it\u2019s important to select data science projects<\/strong> with limited variables and data. The above ones may seem a little challenging, but they should be fun to do.<\/p>\n