Hyperdash vs MHm

Hyperdash is a machine learning monitoring platform built for data scientists. Track the status of your training with real-time alerts and stream console logs from your machine to any device. • Watch the status of your training in real-time • Track full console logs for each training run, past and present • See stack traces if the run fails • Easily contact the developers via text to fix bugs or add features Learn more at hyperdash.io === Hyperdash's open-source Python SDK: === • Supports all python 2.7 and 3.x machine learning libraries, including Keras, Tensorflow, Theano, PyTorch, and more! • Works with both cloud instances and local machines (you can even use both at the same time!) • Security and privacy are paramount to us - your data set never touches our servers === How To Guide === Download our Python SDK (supports 2.7 & 3.x) using pip and signup from the command line: $ pip install hyperdash && hyperdash signup Try a test run: $ hyperdash demo Then use the same email and password to log in to the iPhone app and view your demo run in real-time! Follow the examples and documentation on our website and GitHub page to add Hyperdash to your machine learning project.

The TECOM smart Machine Health management system can be installed on any brand and any electromechanical equipment to provide new generation functions: 1. Equipped with IoT function, connected to TECOM's smart Machine Health management public or private cloud service platform through Ethernet wired or 4G/5G wireless internet access. 2. Can be connected to a smart phone 3. Remote/mobile implementation of functions such as monitoring, notification, alarm, control, trend, analysis, diagnosis, health report and diagnosis report etc. 4. Two-way, Interactive in demand and control operations. All remote monitoring and control functions are controlled by the Private Cloud to ensure the privacy of the electromechanical system.