What did you achieve in your project?

We have achievements in mainly 3 aspects:

1. Polarity Scores
   We cleaned a huge dataset of 39M tweets, and calculated the political polarity scores of users of these tweets.
   Scores are calculated based on the tweets that the user produces (what he/she tweets) and consumes (what their followers tweet).

Let’s use Tensorflow to teach a machine learning algorithm to distinguish between pictures of dogs and pictures of cats!

We usually use the sklearn.cluster.KMeans function to identify clusterings in a dataset.
However, when your clusters aren’t blobs (for example, moons or rings), this function can hardly identify your clusters.
Thus, let’s implement an algorithm to identify difficult clusters!

Let’s create an interactive website with Flask!
The website should do 2 things:

• Allow the user to submit messages to the bank.
• Allow the user to view a sample of the messages currently stored in the bank.

Let’s conduct some webscrapping on the IMDB website!

Let’s make some interactive visualizations for the NOAA-GHCN (global temperature) dataset!

Let’s make a visualization for the Palmer Penguin dataset!

Fortunately, it’s pretty easy to embed interactive HTML figures produced via Plotly on your blog. Just use plotly.io.write_html() to save your figure. Then, copy the resulting HTML file to the _includes directory of your blog. Finally, place the code

In this post, I’ll show how to create a helpful histogram of some synthetic data.