The Most Popular Anaconda Webinars of 2017
Happy holidays, #AnacondaCREW! Our experts love participating in the Python data science community by sharing their experiences through live, interactive webinars. Below are our most-viewed Anaconda webinars of the year. They’re now available on-demand, so even if you missed them the first time around, you can still watch and learn!
Taming the Python Data Visualization Jungle
It’s no secret that Python has a ton of plotting libraries—but which ones should you use? And how should you go about choosing them? Many people end up sticking with whatever library they first encountered, even if there are now much better tools for the job.
Switching libraries might seem daunting, but it doesn’t have to be. Let Peter Wang and Jim Bednar show you how little code you need to write to create beautiful, interactive visualizations. This webinar—the most popular of the year!—takes a workflow-oriented approach: starting with the problems data scientists want to solve through visualization, and then showing you the appropriate tools for solving them. Click here to watch the webinar on demand.
Discover the Next Generation Data Science IDE
In our second most popular webinar of 2017, Team Anaconda presents an overview of JupyterLab, the next generation data science IDE. The latest project from the Jupyter team, JupyterLab offers data scientists the most innovative, cutting edge environment for data science.
Jupyter Notebooks are still core to JupyterLab, but now data scientists can open notebooks, Python/R shells, terminals, data files (CSV, JSON), or scripts from one place. Check out this webinar to see these features in action and learn why JupyterLab is the default experience for Anaconda Enterprise.
Unveiling Anaconda Enterprise 5—The Data Science Platform for the Entire Team
Our goal at Anaconda is to build the best end-to-end platform for data scientists and the organizations they serve. Enterprise data science teams want tools for easily sharing packages, notebooks, and environments, as well as connecting their preferred Python and R environments with Hadoop/Spark clusters. But IT teams also require governed packages and integration with security providers.
To address these challenges, this year we released the latest version of our enterprise data science platform, Anaconda Enterprise 5!
In this webinar, Kris Overholt will show you why Anaconda Enterprise is beloved by both data scientists and IT admins, as well as business analysts and other end-users. He’ll demonstrate key features of the platform, including:
- Quick and easy notebook collaboration with versioning and access control
- One-click scalable, portable, and reproducible data science deployments
- Governance of data science assets via on-premises package repository
- Integration with enterprise identity providers and end-to-end TLS/SSL encryption
- Interactive, distributed computations with Hadoop/Spark clusters
3 Ways to Move Your Data Science Projects to Production
Data scientists often develop projects on their laptops. But while it’s one thing to get your project working on your local machine, it’s quite another to deploy your project to a server.
With Anaconda Enterprise, you can easily productionize your data science projects and applications, and choose the deployment method to use. In this webinar, Kris Overholt and Christine Doig run through three ways data scientists and IT admins solve the deployment challenge, and demonstrate how Anaconda Enterprise empowers users to encapsulate and deploy projects as live applications with a single click. Want to learn more? Check out our whitepaper, Productionizing and Deploying Secure and Scalable Data Science Projects.
Data Science for Big Data with Anaconda Enterprise
Most large enterprises are now using Hadoop or Spark clusters for their big data processing. But Hadoop and Spark require analysts to write in Java or Scala rather than the Python and R languages data scientists prefer.
Installing Anaconda Enterprise on the data nodes in your Hadoop distribution ensures that your data scientists have access to the libraries they need to do their work. In this webinar, we’ll show you how easy Anaconda Enterprise makes it to get your favorite Python and R packages on your Hadoop cluster—without adding a burden to IT.
Revolutionizing Data Science Package Management with Conda
This webinar will show you how Anaconda solved one of the most headache-inducing problems in data science—overcoming the dependency nightmare—through the power of conda.
Powering Anaconda Distribution at its core, our open source, cross-platform package and environment manager is beloved by data scientists because it enables them to easily install and manage their favorite packages from Python and other languages. In addition, data scientists can create virtual conda environments, in which they are free to install Python, pip, and any number of other packages. This means a data scientist can easily flip between projects using Python 2 and Python 3, for example. In this webinar, Travis Oliphant and Kale Franz demonstrate these key features and many more.
Happy New Year!
As you can see, 2017 was a big year for Team Anaconda, and we’re gearing up for an even bigger 2018! We already have a slew of exciting new webinars and other thought pieces in the works—stay tuned!