From theory to practice with our amazing Workshops
The first day of DSPT Day 2019 will be highly directed on getting your hands dirty, with hands-on workshops focused in heterogeneous topics of Data Science. Check the schedule and detailed information below.
NOTE: In order to access any of the public workshops, besides the DSPT Day conference ticket, you also need to acquire the workshop ticket (available soon).
Automated Machine Learning using Auto-sklearn
In this workshop we are going to cover some ideas and general techniques behind automated machine learning like feature discovery, prepossessing, model selection, hyper-parameter optimizations and ensembling.
Familiar with python and sklearn modeling.
R4Journalists: Introduction to data journalism
Everyday, journalists across newsrooms fail to get a new story because they lack the knowledge to deal with data. If you are interested on how data can revolutionize your reporting skills, this workshop is for you.
Assuming that you have never written a line of code, this three hours long workshop will introduce you to the world of data-driven journalism and how code can save you time and enhance your reporting skills.
Using R, a statistical computing and graphics language that can easily get you started on data analysis, we will go across the very basic steps of reporting using data to get you started on the ddj world.
In the end, you should get out of this workshop with the basic knowledge of R language and how to keep developing your data journalism skills.
To participate, you should bring your laptop with R and RStudio already installed. Instructions on how to do it will be provided.
An introduction to Deep Reinforcement Learning
Brief review of Reinforcement Learning (RL) concepts (policies, state-value functions, action-value functions, Q-learning algorithm).
Intuitions on why doing RL with value function approximation (e.g. neural networks) on large state spaces is hard.
Explanation of the DQN algorithm (Mnih 2013), that was used to play Atari games at human level performance.
Implementation of code snippets of DQN with support of a Jupyter notebook with pre-existing Python code skeletons.
Pointers to more recent research papers on extensions to DQN (prioritized replay, double DQN, etc.)
Some familiarity with Machine Learning (e.g. supervised learning, neural networks) is helpful to understand the concepts.
Some familiarity with the Python programming language and either Tensorflow or PyTorch will be needed for writing code snippets.
Tell a story with a map: introduction to information visualization for communication
Information visualization is a very powerful tool when it comes to communication. As an English language adage says – “A picture is worth a thousand words”. Visualization uses one of the most powerful human senses, which is vision, to convey information. Combined with storytelling techniques, visualization can communicate complex information more effectively. A well designed visualization also triggers emotions on the target public, which affects its memorability.
Tools: code editor, local web server.