{"id":18586567,"url":"https://github.com/veb-101/Data-Science-Projects","last_synced_at":"2025-04-10T13:32:08.992Z","repository":{"id":37944749,"uuid":"262149748","full_name":"veb-101/Data-Science-Projects","owner":"veb-101","description":"Collection of data science projects in Python","archived":false,"fork":false,"pushed_at":"2023-11-11T19:46:32.000Z","size":26861,"stargazers_count":1928,"open_issues_count":9,"forks_count":489,"subscribers_count":37,"default_branch":"master","last_synced_at":"2025-04-07T20:08:48.079Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/veb-101.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-05-07T20:17:47.000Z","updated_at":"2025-04-07T00:15:57.000Z","dependencies_parsed_at":"2024-11-12T22:01:57.865Z","dependency_job_id":"32ce7342-8796-41d1-9878-f0f9599cbb4c","html_url":"https://github.com/veb-101/Data-Science-Projects","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/veb-101%2FData-Science-Projects","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/veb-101%2FData-Science-Projects/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/veb-101%2FData-Science-Projects/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/veb-101%2FData-Science-Projects/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/veb-101","download_url":"https://codeload.github.com/veb-101/Data-Science-Projects/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248225709,"owners_count":21068078,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-07T00:38:14.415Z","updated_at":"2025-04-10T13:32:08.959Z","avatar_url":"https://github.com/veb-101.png","language":"Jupyter Notebook","readme":"# Data Science Projects\n\n---\n\n- This is a compiled list of different project topics for learning purposes\n- The main purpose of this list is to get hands-on experience on different topics.\n\n| Sr. No. | Project | Resource link | Completed |\n| ------- | ---------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| | **BASIC** | | |\n| 1 | Sentiment Analysis | \u003col\u003e\u003cli\u003e [Amazon reviews dataset](https://www.kaggle.com/anshulrai/cudnnlstm-implementation-93-7-accuracy) \u003c/li\u003e\u003cli\u003e[Amazon reviews dataset](https://www.kaggle.com/muonneutrino/sentiment-analysis-with-amazon-reviews)\u003c/li\u003e\u003cli\u003e[Twitter Sentiment analysis - Medium](https://towardsdatascience.com/creating-the-twitter-sentiment-analysis-program-in-python-with-naive-bayes-classification-672e5589a7ed)\u003c/li\u003e\u003cli\u003e[Twitter Sentiment analysis - analytics vidhya](https://www.analyticsvidhya.com/blog/2018/07/hands-on-sentiment-analysis-dataset-python/)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 2 | Fake News detection | [Detecting Fake News](https://data-flair.training/blogs/advanced-python-project-detecting-fake-news/) | \u0026#9744; |\n| 3 | Detecting Parkinsons's Disease | \u003col\u003e\u003cli\u003e[Disease detection using XGBoost](https://data-flair.training/blogs/python-machine-learning-project-detecting-parkinson-disease/)\u003c/li\u003e\u003cli\u003e[pyimagesearch - Detecting Parkinsons's Disease](https://www.pyimagesearch.com/2019/04/29/detecting-parkinsons-disease-with-opencv-computer-vision-and-the-spiral-wave-test/)\u003c/li\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 4 | Color Detection | [OpenCV Project](https://data-flair.training/blogs/project-in-python-colour-detection/) | \u0026#9744; |\n| 5 | Iris Data Set - Predict the class of the flower | [many - analytics vidhya](https://repl.it/@LakshayArora1/Iris-Dataset-Logistic-Regression) | \u0026#9745; |\n| 6 | Loan Prediction - Predict if a loan will get approved or not. | [many - analytics vidhya](https://repl.it/@LakshayArora1/Logistic-Regression-Loan-Dataset) | \u0026#9744; |\n| 7 | BigMart Sales Dataset - Predict the sales of a store. | [many - analytics vidhya](https://repl.it/@LakshayArora1/Linear-Regression) | \u0026#9744; |\n| 8 | House Price Regression | [kaggle](https://www.kaggle.com/c/house-prices-advanced-regression-techniques/notebooks) | \u0026#9745; |\n| 9 | Wine quality - Predict the quality of the wine. | [Kaggle kernel](https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009/kernels) | \u0026#9744; |\n| 10 | Heights and Weights Dataset - Predict the height or weight of a person | [Study of height versus weight](https://www3.nd.edu/~steve/computing_with_data/2_Motivation/motivate_ht_wt.html) | \u0026#9744; |\n| 11 | Email Classification | [youtube](https://www.youtube.com/watch?v=exHwwy9kVcg) | \u0026#9744; |\n| 12 | Titanic dataset | \u003col\u003e\u003cli\u003e[Comprehensive data exploration with Python- Kaggle](https://www.kaggle.com/pmarcelino/comprehensive-data-exploration-with-python)\u003c/li\u003e\u003cli\u003e[Titanic Data Science Solutions - Kaggle](https://www.kaggle.com/startupsci/titanic-data-science-solutions)\u003c/li\u003e\u003cli\u003e[Data ScienceTutorial for Beginners - Kaggle](https://www.kaggle.com/kanncaa1/data-sciencetutorial-for-beginners)\u003c/li\u003e\u003cli\u003e[Introduction to Ensembling/Stacking in Python - Kaggle](https://www.kaggle.com/arthurtok/introduction-to-ensembling-stacking-in-python)\u003c/li\u003e\u003cli\u003e[A Data Science Framework: To Achieve 99% Accuracy - Kaggle](https://www.kaggle.com/ldfreeman3/a-data-science-framework-to-achieve-99-accuracy)\u003c/li\u003e\u003cli\u003e[Stacked Regressions : Top 4% on LeaderBoard - Kaggle](https://www.kaggle.com/serigne/stacked-regressions-top-4-on-leaderboard)\u003c/li\u003e\u003cli\u003e[An Interactive Data Science Tutorial - Kaggle](https://www.kaggle.com/helgejo/an-interactive-data-science-tutorial)\u003c/li\u003e\u003cli\u003e[EDA To Prediction(DieTanic) - Kaggle](https://www.kaggle.com/ash316/eda-to-prediction-dietanic)\u003c/li\u003e\u003cli\u003e[Titanic: Machine Learning from Disaster - Kaggle](https://www.kaggle.com/c/titanic)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| | **Intermediate** | | |\n| 1 | Speech Emotion Recognition | [Speech Emotion Recognition with librosa](https://data-flair.training/blogs/python-mini-project-speech-emotion-recognition/) | \u0026#9744; |\n| 2 | Gender and Age Detection | \u003col\u003e\u003cli\u003e[pyimagesearch - Age Detection with deep learning](https://www.pyimagesearch.com/2020/04/13/opencv-age-detection-with-deep-learning/)\u003c/li\u003e\u003cli\u003e[learnopencv - Gender \u0026 Age Classification using OpenCV Deep Learning](https://www.learnopencv.com/age-gender-classification-using-opencv-deep-learning-c-python/)\u003c/li\u003e\u003cli\u003e[DataFlair - Gender and Age Detection with OpenCV](https://data-flair.training/blogs/python-project-gender-age-detection/)\u003c/li\u003e\u003cli\u003e[analytics vidhya - Age Detection](https://www.analyticsvidhya.com/blog/2017/06/hands-on-with-deep-learning-solution-for-age-detection-practice-problem/)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 3 | Driver Drowsiness detection | \u003col\u003e\u003c/li\u003e\u003cli\u003e[Real-time facial landmark detection](https://www.pyimagesearch.com/2017/04/17/real-time-facial-landmark-detection-opencv-python-dlib/)\u003c/li\u003e\u003cli\u003e[Eye blink detection](https://www.pyimagesearch.com/2017/04/24/eye-blink-detection-opencv-python-dlib/)\u003c/li\u003e\u003cli\u003e[Drowsiness detection with OpenCV](https://www.pyimagesearch.com/2017/05/08/drowsiness-detection-opencv/)\u003cli\u003e[DataFlair - System with OpenCV \u0026 Keras](https://data-flair.training/blogs/python-project-driver-drowsiness-detection-system/)\u003c/li\u003e\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e \u003c/ol\u003e |\n| 4 | Basic Chatbot | [chatbot using NLTK \u0026 Keras](https://data-flair.training/blogs/python-chatbot-project/) | \u0026#9744; |\n| 5 | Handwritten Digit Recognition | \u003col\u003e\u003cli\u003e[Handwritten Digit Recognition](https://data-flair.training/blogs/python-deep-learning-project-handwritten-digit-recognition/)\u003c/li\u003e\u003cli\u003e[kaggle - Digit Recognition-Tutorial (CNN)](https://www.kaggle.com/tarunkr/digit-recognition-tutorial-cnn-99-67-accuracy)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 6 | Black Friday Dataset - Predict purchase amount. | [github](https://github.com/rouseguy/BlackFridayDataHack) | \u0026#9744; |\n| 7 | Trip History Dataset - Predict the class of user. | [analytics vidhya](https://www.analyticsvidhya.com/blog/2015/06/solution-kaggle-competition-bike-sharing-demand/) | \u0026#9744; |\n| 8 | Song recommendation | \u003col\u003e\u003cli\u003e[Medium - Simple song recommender system](https://towardsdatascience.com/how-to-build-a-simple-song-recommender-296fcbc8c85)\u003c/li\u003e\u003cli\u003e[Medium - A Simple Song Recommender System in Python](https://towardsdatascience.com/a-simple-song-recommender-system-in-python-tutorial-3e4c111198d6)\u003c/li\u003e\u003cli\u003e[analytics vidhya - Guide to song recommendation system](https://analyticsindiamag.com/beginners-guide-to-building-a-song-recommender-in-python/)\u003c/li\u003e\u003cli\u003e[Youtube - Building Recommender Systems Using Python](https://www.youtube.com/watch?v=39vJRxIPSxw)\u003c/li\u003e\u003cli\u003e[Youtube - Music Search and Recommendation from Millions of Songs](https://www.youtube.com/watch?v=RIW7jjurpPI)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 9 | Handwritten Text Recognition | [Build a Handwritten Text Recognition System using TensorFlow](https://towardsdatascience.com/build-a-handwritten-text-recognition-system-using-tensorflow-2326a3487cd5) | \u0026#9744; |\n| 10 | Sentiment analysis - IMDB movie review dataset | [tensorflow](https://www.tensorflow.org/tutorials/text/text_classification_rnn) | \u0026#9744; |\n| 11 | Text generation - Shakespeare | [tensorflow](https://www.tensorflow.org/tutorials/text/text_generation) | \u0026#9744; |\n| 12 | Sign language MNIST classification | \u003col\u003e\u003cli\u003e[kaggle - Deep learning using sign langugage](https://www.kaggle.com/ranjeetjain3/deep-learning-using-sign-langugage#CNN-Model)\u003c/li\u003e\u003cli\u003e[kaggle - CNN using Keras](https://www.kaggle.com/madz2000/cnn-using-keras-99-7-accuracy)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| | **Advanced** | |\n| 1 | Image Captioning | [Image Captioning with visual Attention](https://www.tensorflow.org/tutorials/text/image_captioning) | \u0026#9745; |\n| 2 | Credit Card Fraud Detection | \u003col\u003e\u003cli\u003e[geeksforgeeks - Credit Card Fraud Detection](https://www.geeksforgeeks.org/ml-credit-card-fraud-detection/)\u003c/li\u003e\u003cli\u003e[Kaggel kernels](https://www.kaggle.com/mlg-ulb/creditcardfraud/kernels)\u003c/li\u003e\u003cli\u003e[Google search results](https://www.google.com/search?q=Credit+Card+Fraud+Detection\u0026rlz=1C1CHBF_enIN820IN820\u0026oq=Credit+Card+Fraud+Detection\u0026aqs=chrome..69i57j69i60\u0026sourceid=chrome\u0026ie=UTF-8)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 3 | Recommendation System | \u003col\u003e\u003cli\u003e[Recommendation Systems](https://engmrk.com/module-18-machine-learning-based-recommendation-systems/?utm_campaign=News\u0026utm_medium=Community\u0026utm_source=DataCamp.com)\u003c/li\u003e\u003cli\u003e[RECOMMENDATION SYSTEM](https://technotipsondatascience.wordpress.com/2018/10/22/recommendation-system/)\u003c/li\u003e\u003cli\u003e[Medium - Movie recommendation](https://towardsdatascience.com/movie-recommender-system-part-1-7f126d2f90e2)\u003c/li\u003e\u003cli\u003e[kaggel - Movies Recommender System](https://www.kaggle.com/rounakbanik/movie-recommender-systems)\u003c/li\u003e\u003cli\u003e[Quick Guide to Build a Recommendation Engine in Python \u0026 R](https://www.analyticsvidhya.com/blog/2016/06/quick-guide-build-recommendation-engine-python/)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 4 | Customer Segmentation | \u003col\u003e\u003cli\u003e[Customer Segmentation by RFM clustering](https://towardsdatascience.com/data-driven-growth-with-python-part-2-customer-segmentation-5c019d150444)\u003c/li\u003e\u003cli\u003e[kaggle - Customer Segmentation](https://www.kaggle.com/fabiendaniel/customer-segmentation)\u003c/li\u003e\u003cli\u003e[Customer Segmentation by KMeans](https://towardsdatascience.com/customer-segmentation-with-machine-learning-a0ac8c3d4d84)\u003c/li\u003e\u003cli\u003e[KDnuggets - Beginner’s Guide to Customer Segmentation](https://www.kdnuggets.com/2017/03/yhat-beginner-guide-customer-segmentation.html)\u003c/li\u003e\u003cli\u003e[KDnuggets - Customer Segmentation Using K Means Clustering](https://www.kdnuggets.com/2019/11/customer-segmentation-using-k-means-clustering.html)\u003c/li\u003e\u003cli\u003e[Customer Segmentation: A Technical Guide](https://www.mktr.ai/applications-and-methods-in-data-science-customer-segmentation/)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 5 | Breast Cancer Classification | \u003col\u003e\u003cli\u003e[pyimagesearch - Breast cancer classification with Keras and Deep Learning](https://www.pyimagesearch.com/2019/02/18/breast-cancer-classification-with-keras-and-deep-learning/)\u003c/li\u003e\u003cli\u003e[Dataflair - Breast Cancer Classification](https://data-flair.training/blogs/project-in-python-breast-cancer-classification/)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 6 | Traffic Signs Recognition | [pyimagesearch - Traffic Sign Classification with Keras and Deep Learning](https://www.pyimagesearch.com/2019/11/04/traffic-sign-classification-with-keras-and-deep-learning/) | \u0026#9745; |\n| 7 | Urban Sound Classification | [Audio Data Analysis using Deep Learning](https://www.analyticsvidhya.com/blog/2017/08/audio-voice-processing-deep-learning/) | \u0026#9744; |\n| 8 | Human Activity Recognition | \u003col\u003e\u003cli\u003e[MLM - Deep Learning Models for Human Activity Recognition](https://machinelearningmastery.com/deep-learning-models-for-human-activity-recognition/)\u003c/li\u003e\u003cli\u003e[Human Activity Recognition with OpenCV and Deep Learning](https://www.pyimagesearch.com/2019/11/25/human-activity-recognition-with-opencv-and-deep-learning/)\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 9 | Covid-19 | \u003col\u003e\u003cli\u003e[pyimagesearch - Covid-19 in X-ray images](https://www.pyimagesearch.com/2020/03/16/detecting-covid-19-in-x-ray-images-with-keras-tensorflow-and-deep-learning/)\u003c/li\u003e\u003cli\u003e[pyimagesearch - Mask detection](https://www.pyimagesearch.com/2020/05/04/covid-19-face-mask-detector-with-opencv-keras-tensorflow-and-deep-learning/)\u003c/li\u003e\u003cli\u003e[rubiks-code Detection of COVID-19 in chest X-Rays with Deep Learning](https://rubikscode.net/2020/03/23/detection-of-covid-19-in-chest-x-rays-with-deep-learning/)\u003c/li\u003e\u003c/ol\u003e | \u003col\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003cli\u003e\u0026#9744;\u003c/li\u003e\u003c/ol\u003e |\n| 10 | Video classification | [pyimagesearch](https://www.pyimagesearch.com/2019/07/15/video-classification-with-keras-and-deep-learning/) | \u0026#9744; |\n| 11 | Fire and smoke detection | [pyimagesearch](https://www.pyimagesearch.com/2019/11/18/fire-and-smoke-detection-with-keras-and-deep-learning/) | \u0026#9744; |\n| 12 | Detecting Natural Disasters | [pyimagesearch](https://www.pyimagesearch.com/2019/11/11/detecting-natural-disasters-with-keras-and-deep-learning/) | \u0026#9744; |\n| 13 | Anonymizing faces | [pyimagesearch](https://www.pyimagesearch.com/2020/04/06/blur-and-anonymize-faces-with-opencv-and-python/) | \u0026#9744; |\n| 14 | Text Summarization | [list of links](https://www.one-tab.com/page/at7XZn6iRsKSgpgNAqK0dw) | \u0026#9744; | | |\n| 15 | Deep Dream and Style Transfer | [list of links](https://www.one-tab.com/page/RYc4BqXSRWOE_A1GIUAPYA) | \u0026#9744; |\n\n## Additional resources\n\n- [A curated list of applied machine learning and data science notebooks and libraries across different industries.](https://github.com/firmai/industry-machine-learning)\n- [edyoda/data-science-complete-tutorial: For extensive instructor led learning](https://github.com/edyoda/data-science-complete-tutorial)\n- [Advanced Data Science - YouTube](https://www.youtube.com/playlist?list=PLegWUnz91Wftp1CsVFQaCgZAILUslEVhF)\n- [Data ScienceTutorial for Beginners | Kaggle](https://www.kaggle.com/kanncaa1/data-sciencetutorial-for-beginners)\n- [donnemartin/data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks)\n","funding_links":[],"categories":["Uncategorized","Data Science ##","Other Awesome Lists"],"sub_categories":["Uncategorized","Comics"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fveb-101%2FData-Science-Projects","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fveb-101%2FData-Science-Projects","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fveb-101%2FData-Science-Projects/lists"}