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Data Science Tools for Solving Daily Problems and Taking
Data Science Tools for Solving Daily Problems and Taking

October 12, 2022

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Introduction

The word "data scientist" is really daunting, don't you think? Like a person who creates data-related innovations to benefit humanity. No! I mean, Yes, it is clear that some individuals have earned doctorates in computing or statistics and who labor tirelessly to develop new algorithms. However, did you know that "Data Science" has been around for a long time but has only recently been given a specific definition?

 

In reality, John W. Tukey stated the following in his book "The Future of Data Analysis" from the year 1962:

 

"I used to think of myself as a statistician, interested in generalizing findings from specific data. But as I've followed the development of mathematical statistics, I've had reasons to ponder and have my doubts. I've come to believe that data analysis is my primary area of interest, and the elements of statistics that conform to it must adopt scientific rather than mathematical features.

 

Here's how Data Science can be used for Taking Decisions

 

  • Personal Movie Recommender System

Netflix will suggest new films to you depending on your viewing habits. There is a restriction, though. Netflix is only able to suggest movies that are already in its catalog. Let's compile a longer list of the films we've seen and

 

You can save yourself all of this trouble by creating a customized movie recommendation system. For a newbie, this may be a little challenging.

However, you may test this out with a different approach if you are familiar with the fundamental ML models. Make a dataset containing all the movies you've seen, their IMDB ratings, genre, star cast, language, director, etc., and assign each one a personal score out of 10. Choose a validating strategy, and employ the right modeling technique on this personal rating as the target variable.

 

Similarly, make a list of all the movies you wish to see and try to acquire the expected ratings for each one using the model that has been fitted above!

 

  • Doing a Self-Analysis

Learn some fundamental methods for text analysis, often known as Natural Language Processing or NLP, and try putting them into practice. To determine how you felt when you sent the message and how frequently you experienced those emotions, perform a sentimental analysis.

 

You recorded your daily activities on paper, right? You may link those activities to your feelings at the end of the day to better understand the kind of activities that make your day more enjoyable.

 

  • Making a chatbot to respond to your pals when you're unavailable

Everything was impacted when the COVID pandemic came out; workplaces had to be shuttered since we were all instructed to stay inside our houses, and call centers and service centers were shut down. Companies have to search for alternatives to make their tasks simpler because of the restricted amount of personnel at their disposal. Many businesses talked to us and recorded our issues using chatbots. The chatbot would provide some solutions if the problem was simple and could be resolved without human intervention.

 

You may create a chatbot that responds on your behalf while you're unavailable. If, while at work, someone contacts you to inquire where you are, you don't have to stop what you're doing to respond; you can simply sit back and do so. The chatbot you build can take care of it for you successfully.

 

  • Researching efficiently before buying anything

When considering a smartphone purchase, you Google "Best phones under 35k." When you click the first link, the blog presents you with five options, and the game of bewilderment begins. Additionally, it doesn't discuss the characteristics that are important to you.

 

Truthfully, only you know what is important to you, and those blogs are written from a general perspective. So how do you pick the greatest option (for yourself) out of thousands of alternatives?

 

Let me explain how an analyst such as you may go about doing that. Make a list of all the different types of cell phones on the market, along with their current costs. If you are familiar with web scraping techniques, you might complete this task quickly.

 

  • Investment

You work hard at your job, yet you still need to save money. And to be honest, if you keep most of your money in your savings account, it won't grow. To be honest, you won't be able to keep up with inflation.

 

Stock investing seems quite sophisticated, no? It's not only for investment bankers, by the way. Anyone can complete it! If you pick the appropriate stocks, you may make as much money in a single month as you would have if you had saved the money in a savings account. Traditional techniques are used, such as qualitative analysis, chart reading, etc.

Conclusion

These are only a few examples of the practical applications of data analytics and data science. However, there are many advantages to developing these talents that you won't even be aware of. You are evolving structure thinking, where chaos is no longer present. Making thoughtful selections would become second nature to you. Decision-making indecision would no longer exist.

 


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