Every Data Scientist spends most of his time in data visualization, preprocessing and model tuning based on the results. These are the toughest situations for every Data Scientist because you will get a good model when you perform all these three steps precisely. There are 10 very helpful jupyter notebook extensions to help in these circumstances. Qgrid is a Jupyter notebook widget which uses SlickGrid to render pandas DataFrames within a Jupyter notebook. This allows you to explore your DataFrames with intuitive scrolling, sorting and filtering controls, as well as edit your DataFrames by double-clicking cells. ITables turns pandas DataFrames and Series into interactive data tables in both your notebooks and their HTML representation.

Mourafiq: This talk is going to be about how to automate machine learning and deep learning workflows and processes. Before I start, I will talk a bit about myself. My name is Mourad [Mourafiq], I have a background in computer science and applied mathematics. I've been involved and working in the tech industry and the banking industry for the last eight years, and I've been involved in different roles involving mathematical modeling, software engineering, data analytics, data science. For the last two years, I've been working on a platform to automate and I manage the whole life cycle of machine learning and the model management, called Polyaxon. Since I will be talking about a lot of processes and best practices and ideas to basically streamline your model managements at work, I'll be referring a lot to Polyaxon as an example of a tool for doing these data science workflows. Several approaches and solutions are based on my own experience developing this tool, and talking with customers and the community users since the platform is open source. Polyaxon is a platform that tries to solve the machine learning life cycle. Basically, it tries to automate as much as possible so that you can iterate as fast as possible on your model production and model deployments. It has a no lock-in feature.

Deep learning might be one of the hottest topics in software development right now. With Polyaxon, managing large scale applications for deep learning and machine learning is easier than ever. Whether you're looking for full control of your data and cluster or simplifying resource management, Polyaxon makes it easier than ever to enable collaboration and stay independent while deploying deep learning applications. Polyaxon allows organizations to build, train, and monitor scalable apps for deep learning with its open source platform. It comes with a built-in set of tools and proven algorithms to let developers start innovating right out of the box.