Different problems that can be solved with Data Science
Data science is not just another business catchphrase. Data science and its algorithms have been bringing steady changes into businesses as well as the daily lives of the global populace. Considering that the world is walking towards data science for the past few years, a lot of growth is expected ahead in the field.
Data science takes the traditional statistics and data analysis forward by focusing on the approach of using data to predict and explain. To derive deeper actionable insights, data is used to learn and construct algorithms based programmes that collect data from various sources and apply hybrid methods. Since data science asks questions from the big unstructured data, this allows companies to make better and informed decisions.
Let us look at different problems that can be solved with today’s superman, aka Data Science.
The language possesses a vast ecosystem of rich libraries and is suitable for multiple purposes makes it versatile. Other features of Python are:
Top Data Science problem-solving Projects
Data science helps in solving real-life problems by using the inputs in the form of useful data information. Data science algorithms help in detecting frauds, climate change, predicting market sales, and even the health conditions of a person. Increased demand for data science has been noted with increased usage of artificial intelligence. A shoot-up has been recorded across the globe in demand for data scientists. Let us have a look at some unusual problems or projects that have been made successful using data science.
Classifying Breast Cancer:
For classifying breast cancer, data science has been used using Python. In the last few decades, breast cancer cases have multiplied, and the only way to overcome this is through early detection of the problem.
With the use of data science, it has become easy to detect IDC or Invasive Ductal Carcinoma in a female chest, which is the standard form of breast cancer. By invading the fibrous and fatty breast tissues which are outside the duct, this health problem develops in the milk duct. For the classification of breast cancer, Deep Learning and Keras library can be used.
OLA Data Analysis:
One of the prevalent taxis in the world is OLA and is serving millions of travellers daily in different cities and different countries. For creating a data science project, ggplot2 along with the R language and data visualisation project can be used. Trips by hours, number of trips in a day, and total trips made in a month, quarter, half-yearly or yearly basis can be taken into consideration with the use of libraries of R language and parameter analysis.
Also, pick up services can be used in a particular region. The results created from the visualisation of different time frames during a year will eventually reveal the impact of customer trips’ time factor.
RecogniSing the speech emotions
To understand the outcome of the marketing plan, product description, political speech, etc., human emotions are considered crucial nowadays. Human emotions that affect the different states from speech and are different states from speech can be recognised with this data science project.
The project aims at recognising the change in human pitch and tone that occurs after hearing a particular topic. To recognise the particular emotion associated with the respective voice tone, MFCC, Chroma, and MEL features are used along with RAVDESS dataset.
Companies are nowadays using sentiment analysis to test the preference and likeability of their products in the market. This analysis aims to get the answer to the following questions:
The method to analyse the people’s opinion on a particular product, service, or decision is taken is defined as sentiment analysis. The array of responses can be kept binary; in some cases, there can be multiple responses as well. The use of R as the programming language in this project helps in analysing the relevant inputs to gain the required information.
RecogniSing fake news
The recognition of fake news detection is often done using Data Science. Today, technology has not only driven the news from the worldwide arena but also promoted fake news from unauthorised sources that had the intention to make mischief or harm the social process and affect the overall interest of the people. Therefore, it becomes really important to detect fake news in time, before it could cause huge damage and harm the gullible. Fake news carries false information that easily becomes hoaxes and spread through the web media and social media channels. This fake news could carry igniting and provoking information about political decisions taken by a rustic, sufferings of individuals during a particular area, and discrimination made by a corporation or manager over its employees.
The main target in such a case is to defame a rustic, company, or people during a particular region which is never good. A knowledge science project using Python is often made to detect fake news during which the model will be created, which may accurately detect if the actual news is real or fake.
Detection of the Parkinson disease
Parkinson’s disease is mentioned as a disease during which the person mostly loses control over body parts. In medical terms, it’s the neurodegenerative and progressive disorder of the central nervous system of a body that affects the regular movement of the body parts and results in stiffness and tremors. This disease’s symptoms and signs include tremor in hands, slowed movement of the body, rigidity, freezing of legs, shuffling steps, mask-like face, and Parkinson gait.
The use of knowledge science might be made to detect paralysis agates within the early stage and gain control over its symptoms and signs. Improvements within the health service are often offered to the patient in this way. The utilisation of knowledge Science might be made for early prediction for Parkinson’s disease and gaining different advantages on the prognosis. The utilisation of Python language might be made during this data science project wherein the conditions of the patients are often tested who are prone or vulnerable or shows signs of Parkinson’s disease.
Credit Card Fraud Detection
Credit Cards are used on the right scale within the present-day world. Almost everyone now carries a credit card that gives its credit facility for shopping for things in any area or region. This has raised chances of fraud as its usage is sort of easy and fraudulence is even more comfortable. To avoid fraud, financial institutions take regular steps.
Creating a knowledge science project to detect credit card fraud is highly useful. During this project, you’ll use the R language alongside algorithms like Decision Trees, ANN, or Artificial Neural Networks, and Logistic Regression. The utilisation of a card transaction dataset is also needed to classify the transaction from being genuine to fraudulent. The addition of various models and plotting of performance curves also can be made during this Data Science Project.
The movie recommendations will be based on the kind of movies watched by a person in the past, his ratings, etc. Their response will often classify the movie as interesting, boring, funny, exciting, or time wastage. Also, the box office performance will guide to urge a thought of the sales that the movie has accomplished within the first few days of opening.
To make a knowledge Science Project for recommending movies, you’ll use the R language to act as recommending movies employing a machine learning process. This machine learning will send suggestions to the users employing a filtering process that’s supported the preferences of other users who have already watched the movie.
The businesses are always trying to find a way to segment their customers so that customer-specific strategies and merchandise placement might be made that most accurately fit their requirements. Suppose you’re the one who features a Data Science Project on Customer Segmentation then you’ll undoubtedly gain a leading-edge advantage over other candidates. Customer segmentation is additionally considered as unsupervised learning during which the utilisation of clusters is formed by the corporate to define and place its customers in several sections supported by age, region, gender, interest, habits, preferences, etc. You’ll use K-means clustering and thereby visualise the age, gender, and other bases of distribution of consumers for segmentation purposes. You’ll utilise the inputs of annual incomes, preferences, and spending scores made by them during a specific period.
How CAN DATA SCIENCE help in business continuity post-COVID-19 pandemic?
COVID-19 pandemic has left the businesses to struggle. The companies are struggling to make the end needs meet, with salary cuts, frozen hiring, layoffs, etc. While businesses are struggling to find their stability again, one thing that ensures a smooth transition of businesses is data science.
Businesses are moving towards data science tools and algorithms to regulate their costs, measure ROI, determine long term impact, optimise their working process, etc. Businesses are also investing their money and time in AI, AR, VR, and Cyber Security technologies that can bring significant transformations to them. Let us have a look at how data science will be playing a crucial to ensure continuity in businesses post-pandemic.
Forecasting and Risk Alleviation:
This pandemic situation has led businesses to be more attentive to the uncertain interruptions and changes that could befall the planet any day. The best way to predict the future, analyse risk, and develop methods to reduce them is data analytics. To analyse a trend and design solutions based on the future anticipated, industries must use historical data. To plan business outcomes during any uncertain phase, companies must rely on it.
Assessing and efficiently using Available Resources:
Data science can help the businesses to make the most of the current situation, along with helping them with forecasting and alleviating the risks. Vigorous analytics can help companies to go through critical equations and find new data related to the current situation. For example, data science can help a financing team to find the changes affecting business during the pandemic and assist them in allocating resources strategically in the coming future.
For business continuity, identifying new opportunities is crucial, and data science can help the companies identify the best possible business opportunities. Identifying gaps and improving them by analysing the available data can help companies move towards identifying opportunities. For example, to understand unique and better ways to support employees in times of crisis, many companies have aggregated COVID case data and combined it with employee data.
Data Security and Data Protection:
Cybersecurity, being an emerging field primarily through the pandemic situation, throws light towards the data vulnerability caused due to an increase in the remote working scenario. To track technical components associated with maintenance and recovery, cloud services are increasingly being used. Also, cybersecurity solutions powered by data science help in monitoring the network traffic across VPNs. Even when employees are working remotely, it allows the companies towards efficient safeguarding of data.
Improvising Services and Offers:
Retail and e-commerce companies are using artificial intelligence and data science to attract customers through offline and online targeting. To get insights into how they can use AI-powered solutions to meet customers’ demands in different areas and optimise their supply chain accordingly. Additionally, an increase in AI chatbots has also been seen recently. Studies have suggested that post-COVID AI chatbot sales will multiply 50 times.
Career as a Data Scientist:
The above stated are the remarkable ways in which data science has helped the day-to-day lives and businesses with its unmatched real-life problem-solving skills and algorithms. While proceeding with data science algorithms, the weaknesses can be removed from the data for efficient usage further. Hence, data science provides opportunities to fill in any observed gaps before making any drastic changes.
Besides helping with the solutions for the problems, data science will also help you keep your abilities ahead as a data scientist. As a data scientist, you will land up your dream job by choosing a particular field you are interested in and learn how to fit in the role well. For example, if you enjoy more working on healthcare projects as a data scientist, you must move your career ahead in a hospital, lab, or pharmaceutical company.
On the contrary, if you find more interest in customer segmentation, you should focus on the corporate sector, enhancing your skills and grooming your abilities as per your interest. Under customer segmentation, you will learn to identify the preference of customers and frame company strategies accordingly. If you find yourself indulged in the IT sector, developing strategies to secure credit cards, you must opt for data science jobs where work will be related to creating related programs and methods.
It is really important to learn data science algorithms, related programming languages, and other skills to help make the world a better place in every certain and uncertain circumstance. The businesses are moving towards using data, to discover insights that can help them make decisions, deliver better products, and create efficient business strategies. Having a data science degree will help you impress hiring managers and land a perfect job.
Considering students’ keen interest nowadays in data science, LEARNXT, in collaboration with SRM, provides students with various data science courses. You can enrol yourself in various MBA, MSc, PG Diploma, and certificate data science courses offered by this collaboration. LEARNXT aims at empowering people to achieve their goals through education. Through case studies, presentations, assignments, and assessments into data science’s practical and theoretical aspects, you will get hands-on experience and insights into the world-class syllabus.
Having a data science degree will help you bag a lucrative job that will also enhance your skills and help you be an experienced data scientist. This world-class collaboration will help you work on yourself, personally and professionally, and will help you become job-ready with real-life projects and experiential learning agendas.
LEARNXT and SRM will help you become a professional with thorough and in-depth knowledge. You will become a professional who will be capable enough to comfortably handle large data sets and who will have deep knowledge of the data science domain.
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