Hi, and Welcome to my GitHub Blog.
＼( *＾ω＾*)／ ﾔｯﾀｰ!
All of my posts here are the memo from my self-study courses, articles, and books. I hope that some of these will help you along in your own journey of learning data science.
If you find the blog posts useful, please give the GitHub blog repo a star to show your support and share it to others. Also, please let me know in the comments section of the posts if you have any questions.
If you would like to subscribe, please click the Subscribe button at the bottom left of the page. Please note that you may have to create or log in to your Feedrabbit (an RSS feed free service), as I use Feedrabbit to send email notifications about new posts.
Thank you! (´･ω･｀)ゞ ｱﾘｶﾞﾄｳ ﾖﾛｼｸ♪.
Posts
Explore a dataset from Kaggle containing a century's worth of Nobel Laureates. Who won? Who got snubbed?
Feb 16, 2022
Build a convolutional neural network to classify images of letters from American Sign Language.
Feb 16, 2022
Use data manipulation and visualization to explore one of two different television broadcast datasets (The Super Bowl and hit sitcom The Office).
Feb 16, 2022
Build a book recommendation system using NLP and the text of books like "On the Origin of Species."
Feb 16, 2022
Reanalyse the data behind one of the most important discoveries of modern medicine which was handwashing.
Feb 16, 2022
In this project, you’ll apply the skills you learned in Introduction to Python and Intermediate Python to solve a real-world data science problem. You’ll press “watch next episode” to discover if Netflix’s movies are getting shorter over time and which guest stars appear in the most popular episode of "The Office", using everything from lists and loops to pandas and matplotlib.
Feb 16, 2022
Build a machine learning model to predict if a credit card application will get approved
Feb 16, 2022
Load, clean, and visualize scraped Google Play Store data to gain insights into the Android app market.
Feb 16, 2022
Open source projects contain entire development histories, such as who made changes, the changes themselves, and code reviews. In this project, Let's find the true Scala experts by exploring its development history in Git and GitHub.
Feb 16, 2022
