In this article, we cover How to install MLflow. Before we dive into the process, let's begin with introducing MLOps By definition, MLOps is a cross-functional, collaborative, and continuous process that focuses on operationalizing data science use cases by managing statistical, machine learning models as reusable, highly available software artifacts via repeatable deployment process. MLOps covers aspects such as model inference, scalability, maintenance, auditing, monitoring, and governance of models in an order that they deliver positive value even as underlying conditions (variables) change. MLOps has grown into prominence to help organizations reduce the risk associated with Data Science, AI, and ML initiatives and maximize returns on analytics. Running ML models and managing its lifecycle needs continuous comparison of the performance of model versions and detection of model drifts, as and when they occur.

Once Anaconda is installed, we need to create and configure our environment. Again, there are many ways to accomplish this. You can complete all the steps using the Anaconda Navigator (graphical interface), but we will use the command line interface, simply because it will give us a better report if and when something goes wrong. If you added Anaconda to your PATH environment during the installation process, then you can run these commands directly from Terminal, Powershell, or CMD. If you didn't, then you can search for and run Anaconda Prompt.

We will be using the Anaconda distribution of Python throughout this course. Using the Anaconda Prompt (you can search for this program after Anaconda has installed), type conda install jupyter to install Jupyter. Jupyter is a notebook style interface for interactive coding. To launch Jupyter, open your Anaconda Prompt and type jupyter notebook. This will launch a new notebook instance in your internet browser.

I'm extremely excited about the new Unity3D Machine Learning functionality that's being added. Setting it up was a little painful though, so I wanted to share the steps I followed, with the specific versions that work (I tried a whole lot and nothing else worked). In this guide, I'll show you everything you need to get setup and ready to start with the 3D ball example. You'll need to download CUDA 8.0.61 for this to work. Close any open Unity and Visual Studio instances (you'll have to restart the installer if you don't do this first) You'll need to create an NVIDIA account and log in to download the library.