Web Scraping with Python

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This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the Python requests, beautifulsoup, retry modules and the browser developer tools. The workshop is intended for users with basic Python knowledge. Anaconda Python 3.5 will be used.

Web Scraping with Python

By |

This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the Python requests, beautifulsoup, retry modules and the browser developer tools. The workshop is intended for users with basic Python knowledge. Anaconda Python 3.5 will be used.

Classification, Regression and Model Selection using Python’s Scikit-learn

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This workshop will introduce participants to machine learning in Python. We’ll start with a brief explanation of Anaconda and the Jupyter notebook environment (although not required for the participant, the instructor will be using these tools). After an introduction to classification, regression and model selection, we’ll use a couple of example datasets to demonstrate how to create, apply and evaluate models in Scikit-learn. Although not required, we recommend all participants to have a basic knowledge of Python.

Data Processing in Python using Pandas

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This workshop will introduce participants to Python’s Pandas. We’ll start with a brief explanation of Anaconda and the Jupyter notebook environment (although not required for the participant, the instructor will be using these tools). After a brief introduction to main Python’s standard data types as well as Pandas data structures, we’ll demonstrate how to retrieve information from Pandas Series and DataFrames. We’ll also demonstrate basic input/output, selection, dropping, sorting, ranking, grouping and apply operations.  Although not required, we recommend all participants to have a basic knowledge of Python.

Intro to Natural Language Processing with Python

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This workshop will provide a quick overview of natural language processing using Python. We’ll cover the basics. Segmenting text into tokens, assigning part-of-speech, assigning dependency labels, detecting and labeling named-entities. We’ll also cover sentiment analysis, topic modelling and maybe some visualizations. The workshop will be conducted in Python and is intended for users with basic Python programming knowledge. Anaconda Python 3.5 and a Jupyter Notebook will be used.

Parallel Processing with Python

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Modern computers have a CPU with multiple cores (usually between 4-8). Come learn how to take advantage of them to parallelize and speed up your code. We’ll show you how to structure your code so you can parallelize it in 5 lines or less. We will also cover some theory, a few practical considerations along with some basic exercises. We’ll be using the multiprocessing module in Python. The workshop is intended for users with basic Python knowledge. The workshop assumes you know how to do the following in Python: i) write a for loop, ii) write a function that has inputs and outputs.  Anaconda Python 3.5 will be used.

A quick introduction to neural networks and a demonstration using PyTorch

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Neural networks are powerful tools that output predictions given data; interesting areas of application include image recognition and autonomous driving.  

In this workshop we introduce the basic concept of neural networks and demonstrate the use of neural networks using “PyTorch.”

PyTorch is one of the efficient Python packages for neural networks, which is designed to be highly flexible and intuitive.

A basic programming experience in Python is helpful to follow the PyTorch examples.  Attendees are also welcome to follow the PyTorch examples on their own laptops during the workshop, in which case it is recommended that PyTorch be installed in advance; see https://github.com/pytorch/pytorch#installation for installation guide.

This workshop is not intended to be comprehensive in terms of kinds of neural networks, optimization algorithms, or neural network frameworks, but rather it is intended to present an overview of conceptual and practical aspects of neural networks.

Web Scraping with Python

By |

This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the requests, beautifulsoup, and retry modules with the browser developer tools. The workshop is intended for users with basic Python knowledge. Anaconda Python 3.5 will be used.

Web Scraping with Python

By |

This workshop will provide an overview of how to scrape data from html pages and website APIs using Python. This will mostly be accomplished using the requests, beautifulsoup, and retry modules with the browser developer tools. The workshop is intended for users with basic Python knowledge. Anaconda Python 3.5 will be used.

Data Science with Social Science data: an introduction to Pandas and StatsModels in Python

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This workshop introduces participants to Python’s NumPy, Pandas DataFrames, Matplotlib and StatsModels using an advertising dataset. Participants will use these tools to model (OLS) associations between advertising expenditures and product sales in example data. We will start with an introductory explanation of Anaconda and the Jupyter notebook environment (although not required for the participant, the instructor will be using these tools). We will proceed with topics including: reading data files; creation, indexing and slicing of Pandas DataFrames; creation and handling of Matplotlib objects; and creation and interpretation of models using Python’s StatsModels. Although not required, we recommend that participants have a basic knowledge of Python.