10 Data Science Projects In Python

10 Data Science Projects In Python

Ready to dive into the world of data science? We’ve put together 10 cool projects using Python. These projects cover different areas like predicting outcomes, understanding sentiments, and classifying images. Whether you’re new to data science or looking to level up your skills, these hands-on projects offer a great way to practice and learn using Python. Let’s get started on your data science journey!

1) Music Recommendation System on KKBox Dataset Python Project for Data Science

Music is everywhere. With over 70 million songs on Spotify alone as of 2021, it’s safe to say music is easily accessible. And there are other services as well like Apple Music, Gaana, Saavn, and KKBox.

However, It is through the Recommendations system that people can discover new songs and acquire new musical tastes. Music streaming services profit from recommendation algorithms as well. It helps them to grow their audience and increase engagement on their platform.KKBox is among Asia’s largest Streaming Services platforms.

2) Natural Language Processing ChatBot with NLTK for Text Classification

Chatbots are those programs that will allow to chat with users about common problems and can reply with adequate information. Several organizations will use these chatbot data science python projects such as the first point of interaction with their customers. 

3) Ola Bike Ride Request Demand Forecast Project on Data Science using Python

Getting ride requests can be tricky because they happen unexpectedly. That’s why it’s important to have a smart algorithm that can predict roughly how many rides we might get soon. This project is all about guessing how many ride requests there will be in a specific area for a certain period.

We identify the area using latitude and longitude, and we measure time in military hours. The aim is to create a good algorithm that can help us plan better for the number of rides we might get.

4) E-Commerce Product Reviews – Pairwise Ranking and Sentiment Analysis

In processing our project’s data, we first detect the language of reviews and exclude those not in our chosen language (e.g., English). We then filter out gibberish reviews, remove profanity, and correct poorly written reviews to ensure grammatical consistency and logical coherence across all texts.

5) Abstractive Text Summarization using the Transformer-BART Model 

Summarisation is very essential in several areas and will find several use cases in everyday life. Some professional experts will write summaries but not every time we will require expert summaries for our products.  The use of Text Summarisation of Python Data projects good-quality jists in an automated fashion will take less time.

6)  Scraping Stock Prices from Yahoo Finance

We have to learn to scrape and clean financial data from Yahoo using several Python libraries. However, this will allow you to understand various components of HTML and how to use that information in extracting certain components of a website. Hence, you can write functions to parse the raw data, select a few stocks, and export the data as a JSON file.

Web Scraping is an important part of data analysts, BI engineers, and data scientist’s jobs. You have to understand various Python tools to create scraping scripts or web spiders for a constant stream of live data from various websites.

7) Instagram Reach Analysis Project

Analytical projects are not about making fancy visualizations, but instead about understanding the data and explaining it in layman’s language. The data scientist needs to clean the data, perform statistical analysis, add data visualization charts, explain the visualization to stakeholders in non-technical language, and perform predictive analysis.

Therefore, in this project, you need to analyze the Instagram dataset, use various visualization graphs to explain the patterns and trends, and finally create a simple machine-learning model to predict the reach of an Instagram post.

8) Flight Price Prediction with Flask App

In this project, you’ll clean the data, explore it, and create visualizations to grasp ticket price trends. You’ll also train, evaluate, and deploy a machine-learning model using Flask. This is an ideal starting point for beginners, offering hands-on experience in data handling and deploying machine-learning solutions.

9) Time Series Analysis and Forecasting of End-to-End Project

In the financial market, there’s a significant demand for time series analysis and forecasting to comprehend patterns, avoid risks, and enhance profits for stakeholders. This project involves data analysis, trend visualization, and developing an improved forecasting strategy.

You’ll then train and assess the ARIMA model, utilizing predictions to compare past and future trends. With a deep dive into time-series analysis, this project is highly recommended for final-year students.

10) Automatic Speech Recognition Project

This project is a bit advanced and took me two months to fully grasp. It involves handling and processing audio and text data to create an automatic speech recognition model. You’ll learn to use HuggingFace transformers to build and enhance multi-language speech recognition models.

Additionally, you’ll gain expertise in cleaning audio and text data and utilizing n-gram language models to improve the WER performance metric.

Conclusion

Great job completing these 10 Data Science projects in Python! You’ve gained practical experience in data analysis, machine learning, and visualization. Now armed with valuable skills, you’re ready for more data-driven adventures. Keep exploring and coding!

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