There is a huge amount of information online, passionate professionals in their respective fields who are more than happy to share their knowledge and thoughts. Books are still my favorite medium to learn in-depth information compare to blogs (ten chapters on one subject vs 1000 words about someone’s opinion). But blogs offer more diversity of point of view and that is a valuable ressource. Here are my picks for this first half of July 2016.
“A Women’s History of Silicon Valley” Celebrating the work of females in the world of Technology, this post goes through the amazing works seven women made for the whole world to become better: Judy Estrin, Lynn Conway, Sandy Kurtzig, Donna Dubinsky, Sandy Lerner, Diane Greene, and … maybe you? The last position is for all the women whose names were forgotten or forgotten to elevate. So, go read about them as they are all had fabulous lives.
Mathematics and Statistics
“Central Limit Theorem” A visually appealing post that explains the famous Central Limit Theorem in easy terms. Isn’t animations so much better than textbook generic definition?
“Data Science interviews: What can you expect?” Without many ressources on the subject online, I found this post on Linkedin to be extremly informative about the whole process of recruiting data scientists.
“The Rectangularness of Countries” Using the programming language R, the author of this post wrote a code that calculates the rectangularness of countries around the world. Supported by pictures, it shows that Egypt is the most rectangular of them all. Nice and fascinating reading about a trivial detail we often don’t notice.
Interactive Instagram Maps for Hong Kong and London: Amazing new tool, this interactive map (for two cities so far) allows the user to check the density of instagram posts by region, to check what brands they are using/promoting, the income of the say people and much more. It also allows zoom-in and filtering, creating an interactive and fun tool for online users to try out.
“A NEURAL NETWORK TRIED TO WRITE A 9TH HARRY POTTER BOOK, AND THE RESULTS ARE HILARIOUS” Did you know that a computer wrote a new Harry Potter book? Using deep learning, Max Deutsch created a robot that can generate a new Harry Potter story by learning about the original work beforehand. Although propbably not as talented as J.K. Rowling, this is still an innovative and fun way of using machine learning.
“10 Takeaways from 22 Data Visualization Practioners at #OpenVisConf” One of the best list-like blog post I saw on medium. The author goes through 10 main elements of data as well as the future we are going into. Fascinating reading and it really made me even more excited about data visualization. Dat aVis is a true form of art.
“Building a data science portfolio: Machine learning project” One of the most in-depth post about how to go through a machine learning project. What are the variables to consider? How to find dataset? How to organize the whole process? This read was extremly interesting and gives great advice for people who wants to start an online portfolio via Github.
“A Gap Year Around the World Taught Me to Appreciate Clichés” The author who traveled freely with no boundaries for a whole year and visited 37 countries do a recap of his trip with his girlfriend. He goes through the cliches he saw and the thoughts he had. It is a summary of a once in a life time experience. TL DR, there is no regrets.
“How Safe is China?” I love reading Qora because you rarily found so in-depth answers in a forum. Here, many people who traveled to China explain their experience in the Asian country (and surprisingly, it is really safe!) China is portrayed as a bad country controled by the communism regim and most foreigners who go there have bad experiences to talk about. At least it seems so based on the media. This is a refreshing take on the question with interesting stats to back it up.
“The Cost Of Losing 30 Pounds” This woman talks about her multiple experiences at losing and gaining weights (often with number 30 pounds). The struggle of a student, a young adult, a more mature adult: she experienced it all. I love that this post is not shy to talk about money invested and time consumed on each of these difficult challenges. She also shares pictures of her process.
“How did the “cool kids” from high school turn out?” Another interesting read. The media likes to say that the cool kids in high school ends up being losers working at MacDonald’s when they grow older. But that is false. The cool kids obviously had charisma and talents to attract others, and hence may (or may not) become successful in life.