Will Kwan spent 50 days to create an AI Startup, out of the project out of Y Combinator Startup School.

You can try it out here: https://omnipost.co.

I’m building a machine learning/SaaS startup. In this video, I share the results my first 50 days of full-time work, explaining my business strategy, showing the core features I designed and programmed, and summarizing what I learned from my users. I also give a overview of all the programming frameworks and API’s I used.

Siraj Raval explores generative modeling technology.

This innovation is changing the face of the Internet as you read this. It’s now possible to design automated systems that can write novels, act as talking heads in videos, and compose music.

In this episode, Siraj explains how generative modeling works by demoing 3 examples that you can try yourself in your web browser. 

In this PyData London talk,  Kevin Lemagnen covers something that I’ve long wondered about: the maintainability of code created in data science projects.

Notebooks are great, they allow to explore your data and prototype models quickly. But they make it hard to follow good software practices. In this tutorial, we will go through a case study.We will see how to refactor our code as a testable and maintainable Python package with entry-points to tune, train and test our model so it can easily be integrated to a CI/CD flow.