More Free Data Sets

@machinelearnbot

After posting my article A Plethora of Data Set Repositories, I received a few messages from people and companies that have also collected a lot of data, and share it with the public. Below are two such sources. Also, you can always find new data sets by searching for data sets on DSC. The data sets that I checked were available in CSC format, and rather small. They can be found here.


More Free Data Sets

@machinelearnbot

After posting my article A Plethora of Data Set Repositories, I received a few messages from people and companies that have also collected a lot of data, and share it with the public. Below are two such sources. Also, you can always find new data sets by searching for data sets on DSC. The data sets that I checked were available in CSC format, and rather small. They can be found here.


More Free Data Sets

@machinelearnbot

After posting my article A Plethora of Data Set Repositories, I received a few messages from people and companies that have also collected a lot of data, and share it with the public. Below are two such sources. Also, you can always find new data sets by searching for data sets on DSC. The data sets that I checked were available in CSC format, and rather small. They can be found here.


Predicting UFC Fights With Machine Learning

#artificialintelligence

As a fan of MMA I often find myself trying to predict the outcome of fights on an upcoming fight card. The problem is that fighting by its nature can be very unpredictable. More so than even boxing, the outcome of an MMA fight can change in a split second, but of course that's what makes it so interesting. All the same I wondered if there was a way to apply modern machine learning techniques to historical fight data and see how a model would perform on new fights. Of course like any ML project I needed data to work with.


Web Scraping in Python using Scrapy (with multiple examples)

#artificialintelligence

The explosion of the internet has been a boon for data enthusiasts. The variety and quantity of data that is available today through the internet is like a treasure trove of secrets and mysteries waiting to be solved. For example, you are planning to travel – how about scraping a few travel recommendation sites, pull out comments about various do to things and see which property is getting a lot of positive responses from the users! The list of use cases is endless. Yet, there is no fixed methodology to extract such data and much of it is unstructured and full of noise.