Data Science

Top 10 Data Science Projects in 2020

Posted in Data Science
Top 10 Data Science Projects in 2020

Data Science is a method that helps in solving real-life problems by utilizing the inputs in the form of relevant data information. They help in detecting frauds, predicting market sales, climate change and even possibilities of heart disease to a person. The increase in usage of Artificial intelligence in the present-day world has observed an increased demand for data science and the role of data scientists has become more crucial. This has brought a shoot up in demand for data scientists around the world.

The companies are using the information retrieved by the data scientist to estimate the product's future, project sales and even try to understand customer behavior so that their business could meet its goals of long term sustenance and growth. The Data Science Certification has been preferred by today's tech-savvy students who want to make their careers in this industry.

However, it's suggested to have some Data Science Projects well placed on your resume to make it more impressive and ascertain your claim of being the top contender for the job position. This is because the hiring managers don't only look for theoretical knowledge but also for the skills that you have gained to solve real-world problems. 

Top Data Science Projects

The following are the top 10 Data Science Projects that could add attraction to your resume.

1. Sentiment Analysis

The sentiment analysis is used by the present-day companies to test the preference and likeability of their products in the market. The main idea is to figure out the answers to the following questions.

  1. Why is the product not liked by the customers?
  2. Why is the product not achieving its target sales?
  3. What reforms can be made in the product to make it acceptable by the majority of the customers?
  4. Which factors affect the sentiments of the customers which can be either product quality, product quantity, product price or any other?

The sentiment analysis is, therefore, a method to analyze the opinion of the people on a particular product, service or decision taken. The opinions can range from positive to negative in polarity. The range of responses can be kept binary like Positive or Negative. In some cases, the responses can be kept with multiple options such as Excited, Happy, No response, Sad, Angry, etc. The data science project can, therefore, make use of language R which can help in attracting the relevant inputs and thereafter analyzing them for gaining the required information from the research work. The use of the latest dataset by JaneaustenR package could also be made in this case. The use of general-purpose lexicons can be made in the sentiment analysis which includes bing, Loughran, and AFINN. Finally, we can build a word cloud that can help in displaying the results.

Source code: Sentiment Analysis Project in R
Language: R
Package: JaneaustenR

2. Recognizing the face news

The recognition of fake news or fake news detection can be done using Data Science. In the present day world, the technology has not only driven the news from the global arena but also promoted fake news from unauthorized sources who had the intention to create mischief or harm the peace process and affect the general interest of the people. Therefore it becomes really important to detect fake news in time before it could cause huge damage and harm around the world. Fake news carries false information that easily becomes hoaxes and spread through the online media and social media channels. These fake news could carry igniting and provoking information about political decisions taken by a country, sufferings of people in a particular area and discrimination made by a company or manager over its employees.

The main target in such a case is to defame a country, company or people in a particular region which is certainly not good. A data science project using Python can be made to detect fake news in which the model will be created which can accurately detect if the particular news is real or fake. You can build a TfidfVectorizer and use a PassiveAggressiveClassifier to analyze the news for being "Real" or "Fake".  The use of JupyterLab can be made in this case with the dataset shape of 7796*4 which could prove highly supportive.

Source Code: Detecting fake news with Python
Language: Python
Package: News.csv

3. Detection of the Parkinson disease

Parkinson's disease is referred to as a disease in which the person mostly the old age loses control over body parts. In medical terms, it is the neurodegenerative and progressive disorder of the central nervous system of a body that affects the regular movement of the body parts and leads to the occurrence of stiffness and tremors. The symptoms and signs of this disease include tremor in hands, slowed movement of the body, rigidity, and freezing of legs, shuffling steps, mask-like face, and Parkinsonian gait.

The use of data science could be made to detect Parkinson's disease in the early stage and gain control over its symptoms and signs. This way an improvement in the health service can be offered to the patient. The use of Data Science could be made for early prediction for Parkinson’s disease and gaining different advantages on the prognosis.  The use of Python language could be made in this data science project wherein the conditions of the patients can be tested who are prone or vulnerable or shows signs to get affected by Parkinson’s disease.

Code: Detecting Parkinson’s Disease with XGBoost
Language: Python
Package: UCI ML Parkinson's dataset

4. Recognizing the speech emotions

Today, human emotions are considered vital to understanding the outcome of the marketing plan, product description, political speech, etc. This way the use of the Librosa library can be made by the Data Scientists to perform the SER or the Speech Emotion Recognition. This data science project will help in recognizing the particular human emotion that is revealed at a particular point of time which has affected the different states from speech.

This way the attempts are made to recognize the voice tone and change in pitch that occurs when a person speaks after listening to the particular subject matter. The use of mfcc, chroma and mel feature along with the RAVDESS dataset to recognize the particular emotion that is associated with the particular voice tone. This way we can build an MLPClassifier for this kind of model.

Code: Speech Emotion Recognition with Librosa
Language: Python
Package: RAVDESS dataset

5. Age and Gender Detection

Age and gender detection is both an interesting and challenging data science project that should form part of your Resume. You need to build a Convolutional Neural Network along with the use of various models trained by Gil Levi and Tal Hassaner for the Adience dataset.

This will help the data science to effectively predict the age and gender of a range of individuals. The only need here will be to introduce Computer Vision and its principles to make this data science project operational. You also need to make use of files such as .caffemodel, .pb, .prototxt and .pbtxt to move ahead efficiently on this data science project.

Code: Age and Gender Detection with OpenCV
Language: Python
Package: Adience

6. OLA data analysis

OLA is one of the very popular taxi services in the world. It serves millions of travelers in different cities daily. The data visualization project with ggplot2 can be used along with the R language for creating a Data Science Project. The use of libraries of R language and analysis of parameters like the trips by hours, number of trips in a day and total trips made by single taxi in a month, quarter, half-yearly or yearly basis can be taken into consideration.

You can use OLA pickup services used by travelers in a particular region and thereby create a visualization of different time frames during a year. The result found will reveal the impact of the time factor on customer trips.

Source Code: OLA Data Analysis Project in R
Language: R
Package: OLA pickups in your city dataset

7. Credit Card Fraud Detection

Credit Cards are used on a wide scale in the present-day world. Almost every person now carries a credit card that offers its credit facility of buying things in any area or region. This has raised chances of fraud of credit card as its usage is quite easy and fraudulence is even easier. Although steps are taken by the financial institutions at regular intervals to avoid credit card frauds the issue continues to rise.

Therefore creating a data science project to detect credit card fraud can prove to be highly useful. In this project, you can use R language along with algorithms like Decision Trees, ANN or Artificial Neural Networks and Logistic Regression. The use of a Card transaction dataset is also needed to be made to classify the credit card transaction from being genuine from a fraudulent. The addition of different models and plotting of performance curves can also be made in this Data Science Project.

Source: Credit Card Fraud Detection using Machine Learning
Language: R
Package: Credit Card transactions dataset

The movie recommendations can be based on the inputs received from the viewers who first watched the movie. Their response can be used to classify the movie as interesting, boring, funny, exciting or even time wastage. Also, the box office performance will guide the observes to get an idea of the sales that the movie has accomplished in the first few days of opening.

To make a Data Science Project for recommending movies, you can use the R language to act in as recommending movies using a machine learning process. This machine learning will send out suggestions to the users using a filtering process that is based on the preferences of other users who have already watched the movie. Also, browsing history information can be used to reveal the attention and craze that has been associated with the movie. 

Source Code: Movie Recommendation System Project in R
Language: R
Package: MovieLens dataset

9. Customer segmentation

The businesses are always looking for a method to segment their customers so that customer-specific strategies and product placement could be made that best suits their requirements. If you are the person who has a Data Science Project on Customer Segmentation than you will certainly gain a cutting edge advantage over other candidates. Customer segmentation is also considered as unsupervised learning in which the use of clusters is made by the company to define and place its customers in different sections based on age, region, gender, interest, habits, preferences, etc. You can use K-means clustering and thereby visualize the age, gender and other bases of distribution of customers for segmentation purposes. You can utilize the inputs of annual incomes, preferences and spending scores made by them during a particular period. 

Source code: Customer segmentation with machine learning
Language: R
Package: Mall_Customers Dataset

10. Classifying Breast Cancer

If you have an interest in creating a medical data science project then you work on the Data Science Project for classifying the Breast Cancer using Python. The present-day era has observed a quick rise in breast cancer cases. The health issue of breast cancer has multiplied in the last decades and the only method to overcome this health issue is through early detection of the problem.

With the use of the IDC_regular dataset, you can create a Data Science Project that will help in detecting the presence of the IDC or Invasive Ductal Carcinoma in the female chest which is the common form of breast cancer. This health problem develops in the milk duct by invading the fibrous and fatty breast tissues which are outside the duct. You can use the Deep Learning and Keras library for the classification of breast cancer.

Source Code: Breast Cancer Classification with Deep Learning
Language: Python
Package: IDC_regular

Do pick your choice from the above Data Science Projects

The above stated are the eye-catching and impressive Data Science Projects that can impress your hiring manager and showcase your abilities and skills to apply your theoretical learnings into real-life problem-solving applications. The above are the ten best Data Science Projects. You pick the ones you feel comfortable with and move ahead in completing them and placing them in your resume to make your hiring manager alert about your skills and talents.

In addition to that, your Data Science Project will give you an insight into your abilities to perform better on the professional front. During the preparation of the Data Science Project, you can identify your strengths and weaknesses and thereby work on removing your weaknesses. Hence an opportunity to fill the gap that you have not observed earlier during your theoretical course can be made.

The Data Science Project will keep ahead of your abilities and help you gain confidence over your self. You will learn that you are fit for this role and become more certain of landing up with your dreamed job. In addition to that working on these Data, Science Projects will reveal your interest in a particular stream. For instance, if you showcase more interest in the data science projects related to medical support than you must move ahead in securing a job in a Pharmaceutical company, Hospital or a research lab.

On the other hand, if you have an interest in creating customer segmentation than you must go ahead in applying for jobs in the corporate sector wherein your abilities and skills can be used as per your interest in identifying customer preferences and tastes so that the corporate strategies can be framed out accordingly. If you are interested in the IT sector and want to develop strategies and methods to secure credit cards than select the credit card related Data Science Project and thereafter apply for a job in the Financial Institution where they will value your abilities and skills to create such programs.

It is certainly up to you to select the Data Science Project of your choice, but it is really important to do a Data Science Project and make it an attraction in your resume. This attraction will surely convince the hiring manager that you have all the required skills and even experienced in the kind of service they are looking for. So, sit back, relax and decide from the top ten Data Science Project stated above which you will work on and make it part of your resume and become ready to impress them so much that they will ask you to join them immediately.

Akhil Bhadwal

Akhil Bhadwal

A Computer Science graduate interested in mixing up imagination and knowledge into enticing words. Been in the big bad world of content writing since 2014. In his free time, Akhil likes to play cards, do guitar jam, and write weird fiction. View all posts by the Author

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