Data science projects to add to your portfolio in 2022

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Data science is becoming more and more popular as a viable career choice nowadays. Any data science project will help you improve your resume. These projects will not only help you gain a deeper understanding of the topics, but will also allow you to gain hands-on experience in the data science industry. It is one of the most intriguing and eye-catching alternatives on the market. Plus, they provide excellent proof of work, and the market is seeing an increase in the need for data scientists.

Build your own portfolio

Students and professionals alike build their own portfolios or work on professional projects posted on different websites. Data science is a broad category of scientific approaches, procedures, techniques, and information retrieval systems used to find meaningful patterns in structured and unstructured data. These initiatives will allow you to network with other professionals in your sector. As more and more industries understand the importance of data science, more opportunities appear on the market.

It is vital to have a variety of tasks to build a professional portfolio. Each project should be well structured and competently managed. If you really want to find out what it’s like to be a pro after having a solid theoretical foundation in data science, now is the time to start working on some hands-on projects. You may also be earning a job based on your delivery talents for a particular project. Consequently, it is vital to learn specialized skills through these assignments. The rise of AI and its possibilities is a blessing, as it ushers in the transformations for which the data science course is so vital. Here are four possible projects to add to your portfolio.

# 1: Chatbot development

Chatbots are important to organizations because they can easily handle a flood of consumer requests and messages. By automating most of the process, they alone reduced the customer service workload. They do this through the use of tools supported by artificial intelligence, machine learning and data science. Chatbots work by analyzing customer input and reacting with a preprogrammed response.

# 2: Detection of fake news

We are sure that the fake news needs no introduction. In today’s interconnected society, it is relatively easy to spread false information on the Internet. Fake news is occasionally spread over the Internet from unauthorized sources, causing problems for the targeted person. To counter the spread of fake news, it is necessary to evaluate the credibility of the material, to which this data science project can help.

# 3: Breast Cancer Classification

Breast cancer cases have increased in recent years and the best way to combat it is to find out early and take appropriate preventive measures. If you want to add a healthcare related project to your portfolio, you can try developing a breast cancer detection system in Python. To create such a system in Python, the model can be trained using the Invasive Ductal Carcinoma (IDC) dataset, which contains histological images of malignant cancer-causing cells. Convolutional neural networks are best suited for this project and Python libraries such as NumPy, OpenCV, TensorFlow, Keras, sci-kit-learn and Matplotlib can be used.

# 4: Detection of sleepiness in drivers

Sleepy drivers are a major cause of road accidents, killing large numbers of people every year. Every year many people die in road accidents and one of the causes of these accidents is sleepiness while driving. Since sleepiness is a possible cause of road hazard, one of the best techniques to avoid it is to install a sleepiness detection system. This project requires the use of a webcam for the system to regularly monitor the driver’s eyes.

Another technology that has the potential to save many lives is a driver drowsiness detection system, which constantly evaluates the driver’s eyes and warns him with alarms if the system detects frequent closing of the eyes. This Python project will require the use of a deep learning model and libraries such as OpenCV, TensorFlow, Pygame and Keras.

Your successful project

There is no successful project without extensive planning, and machine learning is no exception. No data science project is impossible if you have an adequate knowledge of the appropriate tools and procedures. As one of the most in-demand disciplines in the industry, the future of data science has great potential. But, to take advantage of the next prospects, you need to be prepared to face the obstacles that come with it. Therefore, include these machine learning initiatives in your CV to acquire a senior job with higher income and valuable perks.

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