Last week, we wrote an article on workshops in PyCon Montreal 2015- Hands on way to learn Python. Workshops are 3 hour long hands-on tutorials with resources to help audience learn these tools. We hope these videos helped you master Python further.
In this article, we will cover another set of amazing talks from PyCon Montreal 2015. These talks are useful enough to trigger the excitement for getting acquainted with some fantastic features in Python.
The talks are covered in order of complexity. We would recommend beginners to strictly follow the sequence of these talks to avoid feeling lost, others may watch as per their ease.
The best way to start this journey is to watch this talk. Why? Because, this is the problem every analyst would have faced at some point. Got data in form of PDF documents? Missing values? Undefined variables? And you are expected to build a model over and above this!
In this video, Mali explains the fun ways to handle such data and building fantastic models instead of ‘hating them’.
In this video, Sarah explains the extensive use of ‘Bokeh’, a data visualization library apart from matplotlib, d3.js, seaborn used in Python. Sarah also defines the use of bokeh using various methods to make the data look more interactive on web.
Interesting Watch! In this video, Soups Ranjan, Yelp defines how companies are making use of data science techniques in creating advertisements to delight their customers. He also touches upon the processes of ad selection, filtering, machine learning based CTR predictions etc. and eventually justifies the agenda of this talk.
In simple words, Machine learning is an integration of Data Analysis and Automation. If you were looking for the resources to learn Machine Learning, this is a good option to consider. The instructor beautifully explains the concept of machine learning using the automation spectrum that covers the wide spread of ML.
If you don’t know about docker, this video will help. Docker is expected to change the way we look at virtualization and server deployment on the cloud. In this video, Andrew ‘demystifies’ the concepts of an amazing technology known as Docker and gives a brief idea about its working, usage and the future of this technology. Importantly, he shares 5 tips that you should before you try out docker. Check this out.
Git is another tool every data scientist should be hands-on with. For the starters, Github is a website that allows you to upload your git repositories online. Interesting part is, git does not require the use of github. In this video, the advanced level of git has been explained using chapter wise understanding of the commands used in git. This video is more helpful for people who have a basic idea about git & github and are aspiring to conquer the next level.
Steamparse lets you parse real time streams of data. It smoothly integrates Python Code and Apache Storm. In this video, Mr. Andrew flawlessly explains the concept of Storm and how beautifully it works with Python. This session gets concluded with a brief overview of streamparse & pykafka followed by some useful examples.
This talk is focused on understanding the graph database patterns in Python. Elizabeth explains the importance of these patterns followed by explanation of concepts such as Property Graph Definition, Grelim Query Language, Python Pattern for Titan Models, Graph at scale with Cassandra, Elasticsearch, Titan. This talk will give you a fair understanding on this component of Python which you can further refine by personal efforts.
In this article, we have featured the list of best data science related talks from PyCon Montreal 2015. If you have not attended PyCon, you should definitely look at these videos. These talks will not only trigger your interest in doing Data Science on Python, but also tell you about some of the tools which Data Scientists will use in future.
These talks are meant to whet your appetite on various topics. You can learn these concepts further by accessing the plethora of free resources available online. Incase you find any difficulty in learning any concept, feel free to ask our analytics experts here.