There is no such categorization of data science projects as ‘good’ or ‘bad’. The nature of projects that an individual indulges in should depend largely on the stage of the career that the particular person is in. For starters, they are recommended to download any relevant data set from Kaggle, import it to Python, and perform analysis on top of it to generate useful insights.
For advanced users, they can take up projects such as ‘detecting fake news project using Python’, ‘develop a recommendation engine using collaborative filtering using Python’ etc.
For Data Science you can use a good datasetsome great public datasets on which you can make good data analysis and visulization.
Moreover for more Advanced Machine Learning & Deep Learning Projects you can take inspiration from here.
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Well there are n no of Data Scienece Projects
It is basically divided in sub sections like
ML Projects
DL Projects
Data Visualisation Projects
Kaggle Projects
some of them are, Titanic case study,Spam and Ham messages,Breast Cancer prediction and Covid Data Analysis
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How many Data science projects will have to be done for get a job
The amount of Data has grown so much in the recent years and for this reason organisation’s are hiring data scientist so that they can keep tracking the data of their company. But to recruit a Data Scientist, every employer needs a certain experience person or the person who has done something in past related to data scientist.
but to be honest, to secure a job, everyone needs to make their resume stand out from the rest.
Here are the some Data Science Projects which can help you to make your resume more attractive in the data science industry:
- Fake News Detection
- Sentiment Analysis
- Loan Prediction
- Speech Emotion Recognition
- Age and Gender Detection
- Credit Card Fraud Detection
So if you are new in this Data Science field, I recommend you to join some online course where you will get idea How these Projects are prepared and can be done. You may check Board Infinity for best online data science courses.
- Fake News Detection Using Python.
- Data Science Project on Detecting Forest Fire.
- Detection of Road Lane Lines.
- Project on Sentimental Analysis.
- Project on Influences of Climatic Pattern on the food chain supply globally.
THESE ARE SOME PROJECTS FOR BEGINNERS.!!!
Here are a few suggestions:
execute sentiment analysis and create a global cloud out of twitter tweets
Perform stock analysis on specific equities and utilise text mining to explain why particular stocks have had significant price drops. FB and BABA, for example.
Analyze election data from another nation, do a linear regression on home prices, and anticipate how much house values will rise.
You may even create a robot that maps your whole business and extracts data from various sources. This might be handy in businesses with a number of different systems that aren’t linked to one another. Manually linking data from many systems is a pain, especially when certain systems prevent simple access to or download of important data.
It is always up to you to decide what you want to concentrate on. Begin by looking for a position that is a good match for your talents. Here are some videos to aid you in the creation of your final projects.
Great
- Obscure binary search trees
- BSTs following the memoization algorithm
- Heap insertion time
- Optimal treaps with priority-changing parameters
- Research project on k-d trees
- Knight’s travails
- Fast data structures in non-C systems languages
- Search engine for data structures
- Phone directory application using doubly-linked lists
- Spatial indexing with quadtrees
- Graph-based projects on data structures
- Numerical representations with random access lists
- Stack-based text editor
some of the data science projects are:
- Climate Change Impacts on the Global Food Supply.
- Fake News Detection.
- Human Action Recognition.
- Forest Fire Prediction.
- Road Lane Line Detection.
- Recognition of Speech Emotion.
- Gender and Age Detection with Data Science.
- Driver Drowsiness Detection in Python.