Data Science Dojo delivers data science education, consulting, and technical services to harvest the power of data.

Trademarks: This software listing is packaged by Data Science Dojo. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

Jupyter Hub for Machine Learning using Python gives you an effortless coding environment in the cloud with pre-installed Machine Learning python libraries, reducing the burden of installation and maintenance of tasks. Through this offer, a user can work on different applications of Machine Learning including stock market trading, email spam and malware filtering, product recommendations, online customer support, medical diagnosis, online fraud detection, image recognition. The heavy computations required for these applications are not performed on the user’s local machine. Instead, They are performed in the Azure cloud, which increases responsiveness and processing speed.

Following can benefit from our instance:

• Teams of developers
• Data scientists
• Machine learning engineers
• Scientific researcher groups
• And anyone else interested in data science tools

• Pre-installed Machine Learning libraries for python.
• Ready to go notebooks which consist of example codes through which user can get guidance for working on Machine Learning.
• Work with multiple notebooks at the same time.
• Kernel-backed documents enable code in any text file (Markdown, Python, etc.) to be run interactively in Jupyter kernel.
• Code consoles to run code interactively, with full support for rich output.

• Recommended memory: 8GB RAM
• Recommended vCPU:4 vCPUs
• Operating System:Ubuntu 18.04

Our offer provides repositories from following sources:

• Github repository of book Python Machine Learning Book 1st Edition, by author Sebastian Raschka.
• Github repository of book Python Machine Learning Book 2nd Edition , by author Sebastian Raschka.
• Github repository of book Hands on Machine Learning with Scikit Learn, Keras and Tensorflow, by author Geron-Aurelien.
• Github repository of ML for beginners, by Microsoft.

Following Authoring Tools are supported in this offer:

• JupyterHub
• Jupyter Lab
• Terminal

Our instance supports following python libraries:

• pandas
• numpy
• scikit-learn
• mlpack
• matplotlib
• scipy
• Theano
• pycaret
• Orange3
• seaborn

The default port JupyterHub listens to is 8000. You can access the web interface at http://yourip:8000 using the credentials

• username:guest
• password:guest@123