Analytics1305 has built a sophisticated library of machine learning and statistics methods that have been designed from the ground up to be scalable and extremely fast. It contains many of the latest and most advanced algorithms available for the common data analysis tasks of classification, regression, clustering etc. Combining our library with the Amazon EC2 service has given us the opportunity to facilitate its public use. Within a few minutes and a free EC2 account later the analyst can launch multiple machines on the cloud with our libraries pre-installed. Then the data can be uploaded and the required analysis task run. We will provide free support through our documentation, blogs and forums.

1. All Neighbors beta*
   
   
1. Nearest/Furthest
2. K-neighbors/Range-neighbors
3. Exact/Approximate
4. Batch/Progressive
   
5. Single/Dual tree
6. Euclidean/Weighted Euclidean
7. Sparse/Dense/Categorical


2. Kernel Density Estimation beta*
   


1. Gaussian/Epanechnikof kernel
2. Single/Dual tree
3. Exact/Approximate
4. Batch/Progressive
5. Euclidean/Weighted Euclidean
6. Sparse/Dense/Categorical


3. K-means beta*
   
   
1. Tree/Naive
2. Euclidean/Weighted Euclidean
3. Sparse/Dense/Categorical


4. Support Vector Machines beta*
   
   
1. Sparse/Dense/Categorical
2. Gaussian/Polynomial kernel
3. Bootstrap (map-reduce) version
   


5. More to come, subscribe to our newsletter to get updates