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f If you aren’t an avid YouTuber, then you probably haven’t noticed much in the way of changes that have happened on the video-streaming site. On the other hand, if you’re someone who is trying to gain internet fame (and the advertising dollars that go along with it), then odds are you’ve probably encountered a headache lately. According to the new rules, YouTube will no longer allow its users to link to their own websites within the video’s “end card” or the last part of the video unless that video gets 10,000 views. That means most startups, small businesses, Patreons, and other fundraisers trying to promote their brands are at a huge disadvantage getting viewers to their website. Arguably one of the best things about YouTube was how anyone could use it to put themselves or their brands out there and attract attention. Now, not only does your video need to hit the magic 10,000 views number, the account owner must also sign up for the YouTube Partner Program which reg

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Explaining the concept of API in plain English and how to scrape Youtube data using tuber package Last time I talked about strategies for a successful Youtuber. It was such an exciting project for me. But It wasn’t an easy one because I had to struggle with searching for how to get Youtube API key. There are lots of resources already but most of them are for web developers, and tutorials for R users are hardly seeable. After I managed to get the API key spending a whole day, I came across with the idea why not I leave a post for someone who would have the same problem with me. Today I’m going to talk about the concept of API and how to get API key. I will also introduce tuber package for analyzing data in R. If you haven’t used Google APIs and you are interested in doing a data science project with them, this post will be a good start. What is API? If you are unfamiliar with the word API, it could be hard to grasp the meaning of it at first. API stands for Ap

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f R is having quite the growth spurt these days . This popularity may seem peculiar given its statistical roots. However, through the amazing work of Hadley Wickham , and the entire R Studio team, this is changing. One example of this newfound power is being able to write crisp web apps in a laughably minuscule amount of code. In this piece, I’ll walk through how to create a simple wordcloud web app above using just R! No Javascript, HTML or CSS whatsoever. Final project Up & Running Simple ‘Hello World’ with R + Shiny The pathway to Hello World is straightforward. You’ll need to install R. For Mac users the simplest way is Homebrew . If not, you can always get it from CRAN . You get an R console by simply typing R at your terminal of choice. Next, you’ll want to create a file called app.R with the code below. The main driver behind everything we will be doing is an R package called Shiny . What exactly is this magical package? Shiny is

How to use simple Python libraries and built-in capabilities to scrape the web for movie information and store them in a local SQLite database. Photo by Charles Deluvio 🇵🇭🇨🇦 on  Unsplash O ften after a few introductory courses in Python, beginners wonder how to write a cool Python program which demonstrates somewhat advanced capabilities of the language such as web scraping or database manipulation. In this article, I will show how to use simple Python libraries and built-in capabilities to scrape the web for movie information and store them in a local SQLite database, which can later be queried for data analytics with movie info. Think of this as a project to build your own mini IMDB database! This type of data engineering task — gathering from web and building a database connection — is often the first step in a data analytics project. Before you do any cool predictive modeling, you need to master this step. This step is often messy and unstructured i.e.

f The best way to learn data science is by doing it, and there’s no other alternative . From this post, I am going to reflect my learning on how I developed a machine learning model, which can classify movies reviews as positive or negative , and how I embed this model to a Python Flask web application. The ultimate goal is to sail through an end to end project. I firmly believe at the end of this post, you’ll be equipped with all the necessary skill that need to embed an ML model to a web application. I came across this end to project on the book, “ Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition ”[1] by Sebastian Raschka and Vahid Mirjalili. I found this book as a great investment to my data science journey and I encourage you to tryout this book. Kindly note that I am not going in discussing about the theory and concepts in details. To keep this post simple and easy to understand, I’ll provide expl