AI News, PyCon Montreal 2015 tutorials – Hands-on way to learn Data Science in Python
- On Thursday, August 9, 2018
- By Read More
PyCon Montreal 2015 tutorials – Hands-on way to learn Data Science in Python
PyCon(s) carry a benevolent motive of helping the Python community worldwide by providing extensive knowledge resources. I started following PyCon conferences from 2013.
workshops inspired me to follow it back in the year 2014 and this craze continued in 2015 as well.
Workshops aim to provide 3 hour hands on sessions where the instructor also acts as a facilitator.
We recommend beginners to watch these videos in the listed sequence to help understand these concepts better, intermediates &
personally use IPython notebooks for the interactive data exploration and recommend it to every data science professional.
It provides a super basic introduction of notebooks in Python, which then moves on to the explanation of super developed notebooks for Python such as iPython and Jupyter.
This videos demonstrates the methods to make statistical inferences in Python by evaluating the sample, quantifying precision, hypothesis testing and performing similar steps.
This workshop beautifully explains the concept of data visualization supported by various other features (matplotlib) of python which are used to make your visualizations more apt and appealing. It also feature sets of challenges which will definitely excite your grey cells.
This workshop begins with deriving Bayes theorem, then proceeds to the Bayesian statistics followed by solving some real world cases.
It begins with explaining machine learning with scikit-learn, then explains the concepts of supervised and unsupervised learning and eventually, concludes with model validation.
It further deep dives into the concepts of machine learning, thereby, explaining the concepts such as heterogeneous data modelling, text feature extraction, clustering, large scale text classification for sentimental analysis etc.
Here, the instructors has intended to create a contest similar to Kaggle competition among the attendees by forming their groups and helping them with the required tips, tricks, hacks used to solve such questions.
It also covers various practice problems on pandas, DataFrames, setup evaluation functions, test dummy solutions etc.
- On Monday, August 19, 2019
Essential Scala: Six Core Principles for Learning Scala
In this talk I will discuss six fundamental concepts that underly effective Scala. How can programmers quickly and effectively learn to write idiomatic Scala?
[MINI] Primer on Deep Learning
In this episode, we talk about a high-level description of deep learning. Kyle presents a simple game (pictured below), which is more of a puzzle really, to try and ...
Data Provenance and Reproducibility with Pachyderm
Versioning isn't just for source code. Being able to track changes to data is critical for answering questions about data provenance, quality, and reproducibility.
Machine Learning avec Spark, MLLib et D3.js
Cette conférence a pour objet de partager avec les participants le processus d'intégration d'un système de Machine Learning (ML) dans une application Java ...
Making a decision is a complex task. Today's guest Dongho Kim discusses how he and his team at Prowler has been building a platform that will be accessible ...
Expression Oriented Programming with F#
In this session we'll take a deep look at some of the basics of programming: expressions, statements, scope and how we represent data. We'll look at these ...
Distributed Machine Learning 101 using Apache Spark from the Browser
While machine learning has been used for decades, accessibility to these methods is undergoing a radical shift, with the rise of simple interfaces and ...
Functional Data Validation (or How to Think Functionally)
Sooner or later, all developers have to deal with data validation: reading input from the user, checking it, and reporting errors back to the UI. For such a ...
NLP at Scale for Maintenance and Supply Chain Management — Ryan Chandler, Caterpillar
How do you read 100000 documents? The connection between the words we use and things and ideas that they represent can be represented as a structure.
Function-Passing Style, A New Model for Asynchronous and Distributed Programming
In this talk, I'll present some of our ongoing work on a new programming model for asynchronous and distributed programming. For now, we call it ...