# Conferences, webinars, podcasts and the likes

**Shirin's playgRound**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Here, you can find a list of all the talks I gave at conferences, webinars, podcasts, workshops, and all the other places you can and could hear me talk. 🙂

## Workshops I am giving

I offer a workshop on deep learning with Keras and TensorFlow using R. Date and place depend on who and how many people are interested, so please contact me either directly or via the workshop page: https://www.codecentric.de/schulung/deep-learning-mit-keras-und-tensorflow/ (the description is in German but I also offer to give the workshop in English).

## Upcoming talks, webinars, podcasts, etc.

On Wednesday, April 25th 2018 I am going to talk about explainability of machine learning models at the Minds Mastering Machines conference in Cologne.

Deep Learning is one of the “hot” topics in the AI area – a lot of hype, a lot of inflated expectation, but also quite some impressive success stories. As some AI experts already predict that Deep Learning will become “Software 2.0”, it might be a good time to have a closer look at the topic. In this session I will try to give a comprehensive overview of Deep Learning. We will start with a bit of history and some theoretical foundations that we will use to create a little Deep Learning taxonomy. Then we will have a look at current and upcoming application areas: Where can we apply Deep Learning successfully and what does it differentiate from other approaches? Afterwards we will examine the ecosystem: Which tools and libraries are available? What are their strengths and weaknesses? And to complete the session, we will look into some practical code examples and the typical pitfalls of Deep Learning. After this session you will have a much better idea of the why, what and how of Deep Learning, including if and how you might want to apply it to your own work. https://jax.de/big-data-machine-learning/deep-learning-a-primer/

## Past talks, webinars, podcasts, etc.

In January 2018 I was interviewed for a tech podcast where I talked about machine learning, neural nets, why I love R and Rstudio and how I became a Data Scientist.

In December 2017 I talked about Explaining Predictions of Machine Learning Models with LIME at the Münster Data Science Meetup.

In September 2017 I gave a webinar for the Applied Epidemiology Didactic of the University of Wisconsin – Madison titled “From Biology to Industry. A Blogger’s Journey to Data Science.” I talked about how blogging about R and Data Science helped me become a Data Scientist. I also gave a short introduction to Machine Learning, Big Data and Neural Networks.

In March 2017 I gave a webinar for the ISDS R Group about my work on building machine-learning models to predict the course of different diseases. I went over building a model, evaluating its performance, and answering or addressing different disease related questions using machine learning. My talk covered the theory of machine learning as it is applied using R.

**leave a comment**for the author, please follow the link and comment on their blog:

**Shirin's playgRound**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.