Data science is a fast-growing field of computer science with a myriad of applications in the modern world. Data science is a blend of mathematics, statistics and computational algorithms. Python, by far has proved to be one of the best programming languages in which data science algorithms. Let’s take a look at the most notable data science projects built in Python.
Top Data Science Projects in Python
1. Predict Employee Computer Access Needs
In this data science project in Python, data scientists are required to manage the level of access to the data that should be given to an employee in an organization because there are a considerable amount of data which can be misused considering the role of an employee in the company.
The access to the resources and data in the company should be limited in accordance with the role of an employee. Using Data Science, one can build an auto-access model which will minimize the human involvement required to revoke or grant access to the employee and will be done automatically.
2. Music Recommendation Engine
In this data science project, a developer needs to build a music recommendation system where the user is more likely to listen to it. It is done by predicting the chances of listening to the song again by the user after its first observable listening event was triggered within a time window.
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3. Build an Image Classifier for Plant Species Identification
The main goal of this project is to classify and identify the plant into different species of plants using the images of plants. The texture, margin, shape, and features of plants have to be accurately classified into different species of plants.
4. Human Activity Recognition Using Smartphone Data Set
In this data science project, a developer needs to build a classification system where the fitness activities of humans have to be identified accurately. The data is recorded using a smartphone containing embedded inertial sensors on different study participants. The main objective of this project of data science is to classify the activities into one of the events performed, such as laying, standing, sitting, walking downstairs, walking upstairs, walking.
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5. Product Price SuggestionÂ
In this project of data science, one has to build an algorithm for machine learning that can automatically predict the right prices of the products. These product prices have to be suggested using details like item condition, brand name, product category name, etc.
6. Performing Time Series ModellingÂ
In this Data science project, one will need to do Time series forecasting by predicting the requirement of electricity for a particular house. The open-source tool called Prophet is the perfect answer. The Prophet is a forecasting tool that is built by and is used for forecasting trends in future and time series modelling.Â
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7. Credit Card Fraud Detection as a Classification Problem
This project includes the prediction of fraud in credit card transactions using the transactional dataset and predictive models. Due to the increasing number of fraud transactions every day, the financial institution needs to predict the fraud transaction by recognizing the pattern.
8. Predict Quora Question Pairs Meaning using NLP in Python
There are many times on quora that different users will post two or more similar questions with the same meaning or intent which are typed in different words. The main goal of this data science project is to predict which two different quora questions have the same purpose.
This is done using Natural Language Processing (NLP). There will be multiple questions with the same intent, but only one same answer is required for all those similar questions. To avoid duplicate questions and answers, a machine learning algorithm which can solve these types of problem is used by Quora in the real world. Read more about the applications of NLP.
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9. Customer-based Predictive Analytics to Find the Next Best Offer
In this project of machine learning, the developer will need to build a model which can predict the purchase amount of customer against various products. In this way, a company can create personalized offers to the customer against different products.
All companies want to understand the purchase behaviour of a customer and this type of machine learning project is very helpful for them. Lots of data are generated on special sales occasions like Black Friday. This includes information like purchase amount, product category, product id, product details, current city of the customer, type of city customer is staying, marital status of the customer, gender of consumer, age of the consumer, demographics of the customer, etc. All the data are used to offer the customer the next offer, which a customer is more likely to buy.
10. Expedia Hotel Recommendations Data Science Project
In this project of data science, one has to predict and recommend the hotel to the customer where he or she is more likely to book and stay. The main goal of this data science project is to predict the booking outcome for a consumer based on attributes associated with the user event and his search attributes.
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11. Predicting Loan Default
The main goal of this project is to automate the loan eligibility process in real-time based on the details of customers given. One has to predict who is eligible for the loan and who is not likely based on information such as Credit History, Loan Amount, Income, Number of Dependents, Education, Marital Status and Gender.
12. Data Science Project in Python on BigMart Sales Prediction
In this project of data science of Python, a data scientist will need to find out the sales of each product at a given Big Mart store using the predictive model. One will need to build a predictive model for the prediction by understanding the properties of stores and products. The features of stores and products play a vital role in increasing sales of the product.
13. Job Recommendation Challenge-Prediction Â
In this data science project in Python, the main goal of a developer is to build a machine learning model to predict which job user will apply for a job. The information like work history, demographics, and past applications are used to make the prediction for job applying.
Job portals require a better job recommendation engine to create more value for their company where a user can easily find a job he or she needs. These companies want to improve their job recommendation algorithms which is an integral part of their business and to enhance the experience of the user.
14. Classifying Handwritten Digits using MNIST Dataset
In this data science project of python language, a developer will need to build a model in which an image of a handwritten single digit is used to determine what that digit is. One will need to use image recognition techniques, and a machine-learning algorithm to accurately determine that handwritten digits. The developer should focus on increasing the accuracy rate of the prediction of the digit.
15. Explore San Francisco City Employee Salary Data
In this project of data science in Python, a data scientist will need to understand the working of the city government by analyzing the kind of employees it employs and how much they are compensated. This is accomplished by using datasets which contains information like name, job title, compensation given for the period, etc.
16. All-State Insurance Purchase Prediction Challenge Solution
In this Data Science Project, one will need to predict the car insurance policy a customer is more likely to buy after receiving several quotes. The prediction has to be made using the information like quote history and coverage of the insurance. Read more about the applications of Data Science in Banking / Insurance industry.
Conclusion
Here are some of the best data science projects developed using Python. We hope this article has been informative to you.
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Is Python a decent audio programming language?
Librosa and PyAudio are two excellent audio processing packages for Python. Some basic audio functions are also included as built-in modules. It's a Python module for analysing audio signals in general, but it's tailored for music in particular. It comes with everything you'll need to put together a MIR (Music Information Retrieval) system.
Is Python suitable for the study of time series?
In order to prepare data for machine learning models, it must be handled differently and with more care. The employment of a model to predict future values based on previously observed values is known as time series forecasting. Non-stationary data, such as economics, weather, stock prices, and retail sales, are commonly represented as time series. Pandas, a popular Python package, can be used for the majority of this work, and this tutorial will walk you through the process of analysing time-series data with it.
What role does Python play in banking?
Python is an excellent programming language for financial applications. Banks are adopting Python to address quantitative issues for pricing, trade management, and risk management platforms throughout the investment banking and hedge fund industries. Python is being used by banks to tackle quantitative issues in pricing, trading, and risk management, as well as predictive analysis. This language also appears to provide answers to the majority of the financial industry's issues, ranging from analytics and regulation to compliance and data.
