This library includes a few built-in architectures like multilayer perceptrons, multilayer long-short term memory networks (LSTM) or liquid state machines, and a trainer capable of training any given network, which includes built-in training tasks/tests like solving an XOR, completing a Distracted Sequence Recall task or an Embeded Reber Grammar test, so you can easily test and compare the performance of different architectures.
The algorythm implemented by this library has been taken from Derek D. Monner’s paper…”
“It’s getting hard to ignore the importance of data in our lives. Data is critical to the largest social organizations in human history. It can affect even the least consequential of our everyday decisions. And its collection has widespread geopolitical implications. Yet it also seems to be getting easier to ignore the data itself. One estimate suggests that 99.5% of the data our systems collect goes to waste. No one ever analyzes it effectively. Data visualization is a tool that addresses this gap…”
“HOPE is a specialized method-at-a-time JIT compiler written in Python for translating Python source code into C++ and compiles this at runtime. In contrast to other existing JIT compliers, which are designed for general purpose, we have focused our development of the subset of the Python language that is most relevant for astrophysical calculations. By concentrating on this subset, HOPE is able to achieve the highest possible performance
By using HOPE, the user can benefit from being able to write common numerical code in Python and having the performance of compiled implementation. To enable the HOPE JIT compilation, the user needs to add a decorator to the function definition. The package does not require additional information, which ensures that HOPE is as non-intrusive as possible…”
“Bats is a TAP-compliant testing framework for Bash. It provides a simple way to verify that the UNIX programs you write behave as expected.
A Bats test file is a Bash script with special syntax for defining test cases. Under the hood, each test case is just a function with a description…”
“When running a node application in production, you need to keep stability, performance, security, and maintainability in mind. Outlined here is what I think are the best practices for putting node.js into production.
By the end of this guide, this setup will include 3 servers: a load balancer (lb) and 2 app servers (app1 and app2). The load balancer will health check and balance traffic between the servers. The app servers will be using a combination of systemd and node cluster to load balance and route traffic around multiple node processes on the server. Deploys will be a one-line command from the developer’s laptop and cause zero downtime or request failures…”