Algorithm Suggestions for a Self Project So, I am doing a small self project on data analytics. I am collecting the android apps data from the play store sites by web scraping.
I am basically trying to collect all possible information related to a particular app, like it's type/genre and sub-genre, ratings, size, number of downloads, if it's paid/unpaid, and other possible information regarding the apps, wherever possible.

I was wondering after I'm done with the data extraction and cleaning work, what data analytics related algorithms I might be able to apply on my play store apps data to analyze it and find patterns in it, predict the links amongst the data and do other predictions and data analysis on it? 

A few, I came across were :- TFID, Clustering, Decision trees, Sequence Analysis and maybe Regression.

So, please review the above ones and suggest any new algorithms, which might be useful to me for my project. Some specific algorithms under the above mentioned broad algorithm(if there are, which might be useful for this project ) please suggest them. 
Details on them will very much helpful. 

Thanks!
I would start with EDA, as usual. Plot stuff. For categorical data, what counts do you have? For quantitative data, perform the usual summaries and correlations. Since you don't have a question in mind already, I would then move on to unsupervised learning algorithms to suggest patterns in the data. Clustering is definitely a good option here (probably preceded by feature scaling). The unsupervised learning algorithms can lead into supervised algorithms, with all the associated statistical tests.

Without knowing your data, you simply cannot choose algorithms.