Twelve Great Data Science Start-Up Ideas

The data science realm fetches a diversity of technological implements. If you wish to join the cohort of businesses that successfully started to realize the strength of data science into their projects, the market gives you the place to act.

Or if you simply like data science innovations and want to sort out what project to take part in, read further. And here, you can get some clues for your next occupation that will force your assurance in data science and play a key role in your skills’ improvement.

Most Curious Data Science Projects

Data Science comprehension is a bit difficult at first but accompanied by permanent practice, soon you will start to understand most of the complicated terms. Reading professional literature is one of the best ways to get more information about Data Science. One more good method is to take part in a few valuable projects that will raise your qualifications and make your CV more attractive to the recruters.

1. Chatbots Creating. 

Chatbots play a leading role in the business industry because they can fulfill numerous user requests in a moment. As many significant processes became automated, the customer service workload decreased. It became possible due to using methods based on artificial intelligence, and in particular, supervised machine learning techniques.

Chatbots analyze the incoming information from the customer and then respond with a suitable answer. To teach the chatbot, you can use repeated neural networks. And realization can be coded with Python. Aim determines the selection of chatbot type: domain-specific or open-sourced. The more connections these chatbots control, the more intelligent and accurate they become.

2. Credit Card Fraud Detection.

Credit and debit card cheating is the pain for many companies, So, the case is vital for our financial market, and such an advanced solution is in high demand nowadays. We are on our way to covering a billion credit card users by the end of 2022.

In short words, the main idea is to analyze the ordinary consumer’s payment behavior, including places where most of the payments were made, to detect cheating transactions. For this project, you can work with both R and Python. The consumer’s payment history can be used as incoming information and later used in Artificial Neural Networks, and logistic regression is the right method for deeper analysis. The more information you provide for the NN, the more accurate the results will be.

3. Fake News Identification.

In the current all-connected reality, fake news injection into the internet has become very simple. From time to time, every person can see false information on the popular internet media which was published based on the data from unauthorized sources. Distribution of fakes can be an object of the trial in court with high financial and reputational losses.

Detecting false information is vital to handling the spread of fake news. And it could be done with the assistance of AI technologies. To divide the false information from the real one, you can use Python and build a model with PassiveAggressiveClassifier. If you need the dataset to teach your ML model, News.csv can be a proper dataset. Check this collection of the best free databases for your ML project here.

4. Forest Fire Prediction

The creation of a forest fire and wildfire prediction mechanism is one more application of the possibilities given by Data Science. Each forest fire accident causes great harm to nature, animals, and human possessions.

To control the unpredictable character of wildfire, you may use k-means clustering to find the main reason for ignition. It is helpful for the proper resource to apportion. Also, if you want to improve your prediction mechanism, you can use the meteorological information to find mutual phases.

5. Breast Cancer Categorization.

If you want to attach a healthcare project to your portfolio, you can make a breast cancer identifying system via Python. Unfortunately, breast cancer has spread lately, and one of the best ways to fight it is to detect it in the very beginning and take preventive actions.

IDC(Invasive Ductal Carcinoma) information, which includes pictures of cancer-including cells, can be helpful to create such a system using Python. NumPy, OpenCV, TensorFlow, Keras, sci-kit-learn, and Matplotlib can also be useful for this project.

6. Driver Drowsiness Identifying.

One of the main reasons for people’s deaths is traffic accidents and, sadly, sleepy drivers are the cause of some of them. So, the solution to this problem is to implement a detection system.

A driver’s sleepiness identifying system could potentially save many lives by alarming after detecting the closed eyes of the driver.

A web camera is a necessary device for this project for a system to identify close eyes. OpenCV, TensorFlow, Pygame, and Keras are good models for that.

7. Systems of recommendation.

Have you ever thought about ways of social media like YouTube or Netflix to analyze your tastes and give you recommendations? These services use a special recommendation system. They need some characteristics: your preferences, according to what you have watched before, your age, rating of your favorite movies, and many others. After that, services transport that information into the ML model and give you proper recommendations.

Using your preferences and incoming information, you have an opportunity to create your recommendation system. You can choose R for this project because it includes more than 58000 movies.

8. Sentiment Analysis.

Sentiment analysis is known as opinion mining. It is an instrument supported by AI, which allows you to explore a person’s points of view. These points of view about a product could come from different sources, like surveys or reviews.

Contemporary companies, which manage data, get a lot of advantages from opinions analysis because they can see people’s reactions to new products. To find out, how to desing such kind of system, check this explanation of sentiment analysis.

​​9. Exploratory Data Analysis.

Exploratory is the beginning of Data Analysis. It helps to understand the information, and it also includes visualization. There are a few options to visualize – scatterplots, heat maps, and histograms. Sometimes you can get unexpected results via EDA, be ready for this.

10. Gender Detection & Age Prediction.

This project aims to identify and predict human gender. This project aims to create a system that detects a person’s age and gender via the image.

Here you can use Python with the OpenCV package. But be careful! Such things as make-up, lighting, and emotions can confuse the program.

11. Recognizing Speech Emotions.

Speech is one of the most crucial instruments of expressing personality. It includes a variety of emotions: happiness, sadness, anger, and humility. Having information about feelings, you have an opportunity to analyze future actions and offer specific and personalized services and products to consumers.

This project aims to detect emotions and feelings from different sound attachments that include people’s speech.

12. Customer Segmentation.

Now businesses try to provide personalized products and services to their consumers. And, of course, they have to create categories and segments to do this.

Of course, to make this project possible, you have to divide your consumers into categories according to their age, interest, solvency, etc. Mall_Customers can be effective for this project.

For sure, there are a lot of projects to create. Examples are Climate change or Coronavirus visualization, Parkinson’s Disease identification, etc.

In conclusion

With this collection of the most interesting Data Science project ideas, you can open your own business or take part in any to widen your portfolio and become a successful data scientist.

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