Here is the list of few projects (found on kaggle). They cover Basics of Python, Advanced Statistics, Supervised Learning (Regression and Classification problems) & Data Science
Please also check the discussions and notebook submissions for different approaches and solution after you tried yourself.
1. Basic python and statistics
Pima Indians :- https://www.kaggle.com/uciml/pima-indians-diabetes-database
Cardio Goodness fit :- https://www.kaggle.com/saurav9786/cardiogoodfitness
Automobile :- https://www.kaggle.com/toramky/automobile-dataset
2. Advanced Statistics
Game of Thrones:-https://www.kaggle.com/mylesoneill/game-of-thrones
World University Ranking:-https://www.kaggle.com/mylesoneill/world-university-rankings
IMDB Movie Dataset:- https://www.kaggle.com/carolzhangdc/imdb-5000-movie-dataset
3. Supervised Learning
a) Regression Problems
How much did it rain :- https://www.kaggle.com/c/how-much-did-it-rain-ii/overview
Inventory Demand:- https://www.kaggle.com/c/grupo-bimbo-inventory-demand
Property Inspection predictiion:- https://www.kaggle.com/c/liberty-mutual-group-property-inspection-prediction
Restaurant Revenue prediction:- https://www.kaggle.com/c/restaurant-revenue-prediction/data
IMDB Box office Prediction:-https://www.kaggle.com/c/tmdb-box-office-prediction/overview
b) Classification problems
Employee Access challenge :- https://www.kaggle.com/c/amazon-employee-access-challenge/overview
Titanic :- https://www.kaggle.com/c/titanic
San Francisco crime:- https://www.kaggle.com/c/sf-crime
Customer satisfcation:-https://www.kaggle.com/c/santander-customer-satisfaction
Trip type classification:- https://www.kaggle.com/c/walmart-recruiting-trip-type-classification
Categorize cusine:- https://www.kaggle.com/c/whats-cooking
4. Some helpful Data science projects for beginners
https://www.kaggle.com/c/house-prices-advanced-regression-techniques
https://www.kaggle.com/c/digit-recognizer
https://www.kaggle.com/c/titanic
5. Intermediate Level Data science Projects
Black Friday Data : https://www.kaggle.com/sdolezel/black-friday
Human Activity Recognition Data : https://www.kaggle.com/uciml/human-activity-recognition-with-smartphones
Trip History Data : https://www.kaggle.com/pronto/cycle-share-dataset
Million Song Data : https://www.kaggle.com/c/msdchallenge
Census Income Data : https://www.kaggle.com/c/census-income/data
Movie Lens Data : https://www.kaggle.com/grouplens/movielens-20m-dataset
Twitter Classification Data : https://www.kaggle.com/c/twitter-sentiment-analysis2
Share with credits: https://news.1rj.ru/str/sqlproject
ENJOY LEARNING 👍👍
Please also check the discussions and notebook submissions for different approaches and solution after you tried yourself.
1. Basic python and statistics
Pima Indians :- https://www.kaggle.com/uciml/pima-indians-diabetes-database
Cardio Goodness fit :- https://www.kaggle.com/saurav9786/cardiogoodfitness
Automobile :- https://www.kaggle.com/toramky/automobile-dataset
2. Advanced Statistics
Game of Thrones:-https://www.kaggle.com/mylesoneill/game-of-thrones
World University Ranking:-https://www.kaggle.com/mylesoneill/world-university-rankings
IMDB Movie Dataset:- https://www.kaggle.com/carolzhangdc/imdb-5000-movie-dataset
3. Supervised Learning
a) Regression Problems
How much did it rain :- https://www.kaggle.com/c/how-much-did-it-rain-ii/overview
Inventory Demand:- https://www.kaggle.com/c/grupo-bimbo-inventory-demand
Property Inspection predictiion:- https://www.kaggle.com/c/liberty-mutual-group-property-inspection-prediction
Restaurant Revenue prediction:- https://www.kaggle.com/c/restaurant-revenue-prediction/data
IMDB Box office Prediction:-https://www.kaggle.com/c/tmdb-box-office-prediction/overview
b) Classification problems
Employee Access challenge :- https://www.kaggle.com/c/amazon-employee-access-challenge/overview
Titanic :- https://www.kaggle.com/c/titanic
San Francisco crime:- https://www.kaggle.com/c/sf-crime
Customer satisfcation:-https://www.kaggle.com/c/santander-customer-satisfaction
Trip type classification:- https://www.kaggle.com/c/walmart-recruiting-trip-type-classification
Categorize cusine:- https://www.kaggle.com/c/whats-cooking
4. Some helpful Data science projects for beginners
https://www.kaggle.com/c/house-prices-advanced-regression-techniques
https://www.kaggle.com/c/digit-recognizer
https://www.kaggle.com/c/titanic
5. Intermediate Level Data science Projects
Black Friday Data : https://www.kaggle.com/sdolezel/black-friday
Human Activity Recognition Data : https://www.kaggle.com/uciml/human-activity-recognition-with-smartphones
Trip History Data : https://www.kaggle.com/pronto/cycle-share-dataset
Million Song Data : https://www.kaggle.com/c/msdchallenge
Census Income Data : https://www.kaggle.com/c/census-income/data
Movie Lens Data : https://www.kaggle.com/grouplens/movielens-20m-dataset
Twitter Classification Data : https://www.kaggle.com/c/twitter-sentiment-analysis2
Share with credits: https://news.1rj.ru/str/sqlproject
ENJOY LEARNING 👍👍
👍5
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3. JavaScript ➝
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ENJOY LEARNING👍👍
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Many people pay too much to learn Python, but my mission is to break down barriers. I have shared complete learning series to learn Python from scratch.
Here are the links to the Python series
Complete Python Topics for Data Analyst: https://news.1rj.ru/str/sqlspecialist/548
Part-1: https://news.1rj.ru/str/sqlspecialist/562
Part-2: https://news.1rj.ru/str/sqlspecialist/564
Part-3: https://news.1rj.ru/str/sqlspecialist/565
Part-4: https://news.1rj.ru/str/sqlspecialist/566
Part-5: https://news.1rj.ru/str/sqlspecialist/568
Part-6: https://news.1rj.ru/str/sqlspecialist/570
Part-7: https://news.1rj.ru/str/sqlspecialist/571
Part-8: https://news.1rj.ru/str/sqlspecialist/572
Part-9: https://news.1rj.ru/str/sqlspecialist/578
Part-10: https://news.1rj.ru/str/sqlspecialist/577
Part-11: https://news.1rj.ru/str/sqlspecialist/578
Part-12:
https://news.1rj.ru/str/sqlspecialist/581
Part-13: https://news.1rj.ru/str/sqlspecialist/583
Part-14: https://news.1rj.ru/str/sqlspecialist/584
Part-15: https://news.1rj.ru/str/sqlspecialist/585
I saw a lot of big influencers copy pasting my content after removing the credits. It's absolutely fine for me as more people are getting free education because of my content.
But I will really appreciate if you share credits for the time and efforts I put in to create such valuable content. I hope you can understand.
Complete SQL Topics for Data Analysts: https://news.1rj.ru/str/sqlspecialist/523
Complete Power BI Topics for Data Analysts: https://news.1rj.ru/str/sqlspecialist/588
I'll continue with learning series on Excel & Tableau.
Thanks to all who support our channel and share the content with proper credits. You guys are really amazing.
Hope it helps :)
Here are the links to the Python series
Complete Python Topics for Data Analyst: https://news.1rj.ru/str/sqlspecialist/548
Part-1: https://news.1rj.ru/str/sqlspecialist/562
Part-2: https://news.1rj.ru/str/sqlspecialist/564
Part-3: https://news.1rj.ru/str/sqlspecialist/565
Part-4: https://news.1rj.ru/str/sqlspecialist/566
Part-5: https://news.1rj.ru/str/sqlspecialist/568
Part-6: https://news.1rj.ru/str/sqlspecialist/570
Part-7: https://news.1rj.ru/str/sqlspecialist/571
Part-8: https://news.1rj.ru/str/sqlspecialist/572
Part-9: https://news.1rj.ru/str/sqlspecialist/578
Part-10: https://news.1rj.ru/str/sqlspecialist/577
Part-11: https://news.1rj.ru/str/sqlspecialist/578
Part-12:
https://news.1rj.ru/str/sqlspecialist/581
Part-13: https://news.1rj.ru/str/sqlspecialist/583
Part-14: https://news.1rj.ru/str/sqlspecialist/584
Part-15: https://news.1rj.ru/str/sqlspecialist/585
I saw a lot of big influencers copy pasting my content after removing the credits. It's absolutely fine for me as more people are getting free education because of my content.
But I will really appreciate if you share credits for the time and efforts I put in to create such valuable content. I hope you can understand.
Complete SQL Topics for Data Analysts: https://news.1rj.ru/str/sqlspecialist/523
Complete Power BI Topics for Data Analysts: https://news.1rj.ru/str/sqlspecialist/588
I'll continue with learning series on Excel & Tableau.
Thanks to all who support our channel and share the content with proper credits. You guys are really amazing.
Hope it helps :)
👍5