# Talks and Presentations

## :calendar\_spiral: Timeline

SLM Lab has been used by the authors for giving talks and tutorials on deep RL at a number of meetup groups. All these previous talks along with their free resources are listed below:

* **5 Nov 2016**, NYC Data Wranglers @ Eligible Inc, NYC: [Reinforcement Learning](https://www.meetup.com/NYC-Data-Wranglers/events/235116457/)
  * video: [Reinforcement Learning - Eligible HQ, Part 1 - YouTube](https://www.youtube.com/watch?v=qBhLoeijgtA)
  * video: [Reinforcement Learning, Part 2 - YouTube](https://www.youtube.com/watch?v=wNSlZJGdodE)
* **4 April 2017**, NYC Data Wranglers @ SquareSpace, NYC: [Introducing OpenAI Lab for Reinforcement Learning | Meetup](https://www.meetup.com/NYC-Data-Wranglers/events/238345289/)
* **18 May 2017**, NYC Data Wranglers @ PaperSpace, NYC: [ML at Work #1: Adversarial Autoencoders, Insight Data Science, and more! | Meetup](https://www.meetup.com/Machine-Learning-at-Work/events/239568811/)
* **19 Dec 2017**, DLSG @ Untapt, NYC: [“OpenAI Lab” for Deep Reinforcement Learning Experimentation](https://insights.untapt.com/openai-lab-for-deep-reinforcement-learning-experimentation-6287867eb611)
* **17 Feb 2018**, DLSG @ Untapt, NYC: [Deep Reinforcement Learning Experiments Run Simultaneously Across OpenAI and Unity Environments](https://insights.untapt.com/deep-reinforcement-learning-experiments-run-simultaneously-across-openai-and-unity-environments-62587b89e8ee)
* **15 March 2018**, PyData SLO @ Cal Poly, San Louis Obispo: [Deep RL in PyTorch](https://www.meetup.com/fr-FR/PydataSLO/events/259150102/)
* **2 Oct 2018**, @ PyTorch Developer Conference, San Francisco: [Poster Presentation](https://github.com/kengz/pytorch-conference/blob/master/SLM%20Lab%20PyTorch%20poster%202018.pdf)
* **10 Oct 2019**, @ PyTorch Developer Conference, San Francisco: [Poster Presentation](https://github.com/kengz/pytorch-conference/blob/master/SLM%20Lab%20PyTorch%20poster%202019.pdf)

{% hint style="info" %}
SLM Lab was previously "OpenAI Lab", which has no affiliation to OpenAI.
{% endhint %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://slm-lab.gitbook.io/slm-lab/master/publications-and-talks/talks-given-with-slm-lab.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
