WWCodePython Save

Click on a logo below to view the associated repo -- where you can review, copy, or clone the repo's content. Please reach out with any questions or issues, and/or join us on Slack for interactive discussions and support.

This hands-on workshop will guide you in building potential resume python projects on web development, data analytics, and cloud development. As we lay out the path to boosting your resume effectively, we invite you to join us on this journey.

Project List:

• Traffic Log
• Expense Tracker
• Sales Insight Project

- By Elaine Chan, Mansi, Chethana

Have you ever wondered how a search button work? Do you know your mutli-lingual ability can be extended to exporting in finding specific information you want online?

For beginners with fundamental Python knowledge, we will cover Basic RegEx Structure, introduction of Regular Expression and Language, Metacharacter, RegEx methods, & fun regex games in the 5-part series

- By Karen Wong, Mansi Jain and Katerina Hanson

Join us for an exciting series that will introduce you to some of the popular coding environments used for Python, including: Google Colab, Jupyter notebooks, Visual Studio Code, PyCharm, Vim, Anaconda, and more!

- By Poojita Garg, Jessica Koubi and Nayeon Shin

Join our Introduction to Qt series to learn how to create your first interface with PyQt/PySide! We will go over how to create simple interfaces, some of Qt concepts, and how to put everything together to create a more complex interface.

- By Jessica Koubi

These Python one-liners will save you a bunch of time on your next project, so make sure to come along with us on this journey to uncover the true potential of the Python language and learn how to✨ do a lot with a little✨.

- By Poojita Garg and Karen Wong

While traditional encodings to convert words and sentences to vectors were more intuitive, static embeddings were developed to incorporate a large vocabulary and corpus and eliminating the problem of sparse vectors. Since then, we’ve seen methods like word2vec, GloVe and now contextual embeddings are the norm - Elmo and now the state-of-the-art BERT.

In this talk, we’ll be covering how to create these embeddings with a focus on the most recent development - BERT, using the HuggingFace Transformers Library. We shall also cover how we can obtain BERT multilingual embeddings and how these embeddings are useful in a seq2seq network - which is a specific type of neural architecture to convert sequence of words or characters to another sequence

- By Shreya Khurana

Unit tests are great, but they don’t catch all bugs because they don’t test features like a user -- but Web UI tests are complicated & notoriously unreliable. How can we write tests that do the job well? Never fear! :star2: :star2: :star2:

Let’s learn how to write robust, scalable Web UI tests using Python, pytest, & Selenium WebDriver that cover the full stack for any Web app:

• Using Selenium WebDriver like a pro
• Modeling Web UI interactions in Python code
• Writing “good” feature tests that are efficient, robust, and readable
• Deciding what should and should not be tested with automation

In this talk, we'll write one simple test together that covers DuckDuckGo searching. Afterwards, you’ll know how to write battle-hardened Web UI tests for any Web app, including Django & Flask apps. Example code will be supplied on GitHub, as well as plenty of hands-on tutorials & resources to continue learning!

- By Andrew Knight

Most of the time, Python is seen as object-oriented -- a style where we model our data in the form of classes, objects, & methods. But Python supports alternatives to that OOP paradigm -- Functional Programming being a very popular choice.

Functions like lambda , filter, map, & reduce fully support the Functional Programming style & in this live coding session we'll demonstrate how they can be effectively & efficiently used in our data analysis tasks.

Here are some good reads on Functional Programming, to get your started :

1. Don't be Scared of Functional Programming
2. Functional Programming (Python Docs)
   
   - By Parul Pandey

Have you ever started a data science project and not known what to do next? Are you just curious about what a data scientist actually spends most of their time doing?

Join us to learn all about Exploratory Data Analysis (EDA) - the process of cleaning, organizing, & understanding your data.

During this talk we'll be covering how to import & organize data with pandas, make beautiful visualizations using Seaborn, & use some core Python as well! 🌟

- By Ashley Steele

Apache Spark is currently one of the most popular systems for large-scale data processing - making it a standard for any developer or data scientist interested in big data. Spark supports multiple widely used programming languages(Scala, Python, R, Java) and a wealth of built-in and third-party libraries.

In Session I you will be introduced to Apache Spark main concepts & you'll learn how to leverage the DataFrame API to extract data. You will also learn how to connect to different sources, apply schemas when reading data, and handle corrupt records.

PART I:

In session II you will be introduced to some of the most useful transformations - adding new columns, casting column types, renaming columns, etc. You'll also learn how to define User Defined Functions to do your own custom transformations & a get a little introduction to executing your own ad hoc SQL!

PART II:

In session III you'll analyze the robberies data by doing some aggregations & sorting. You'll learn how to convert Spark DataFrames to Pandas DataFrames. Additionally, you'll explore joins & lookup tables & write final results to CSV files. At the end of this session we'll go over best practices.

PART III:

A Web Application helping Doctors & medical personnel detect & diagnose Respiratory/Lung Diseases using CXR (X-Ray data) images.

A Strictly Medical Machine-Learning based solution with a special implementation of a CNN (convolutional neural network).

- by Vishwa Mehta

Python, data, matrices, transformations & all things Numpy! Join Yashika as she covers the basics of this powerful & essential Data Science library that underpins Pandas, Matplotlib, Seaborn, & many many others.

- by Yashika Sharma

Python:exclamation:Python:exclamation:Python:exclamation:
Let me show you how to use SciKit to do an Emoji :laughing: :open_mouth: :grin: Predictor with a little Machine Learning & Python. 🌈 Learn a few ML & NLP (Natural Language Processing) core concepts ........We do it because we can.:star:

- by Alex Gamez, Software Engineer @ Lockheed Martin Aeronautics :rocket:

Come study all the delightful data and play with Pandas!
Increase your Python data manipulation skills for fun and profit.

Titanic Machine Learning webinar 7/30/2019

Do you want to rank in the top 10% in a Kaggle Competition? Explore the Titanic Dataset & get a taste of Exploratory Analysis & Machine Learning Prediction with Python.

Titanic Icon by Anbileru Adaleru, from The Noun Project. thenounproject.com

Aprende los conceptos relacionados con la internacionalización de aplicaciones web con ejemplo traducción del contenido estatico y dinamico de un sitio web.

Using Jupyter Notebook, Pandas, and Matplotlib to create a framework for teaching data science in a scientific context. Download the presentation and resources here.

Join us alternating Mondays for a wholesome & healthy dose of ML 🌟. -- Starting off with a whirlwind review of Python & then diving into foundational libraries.

We'll also be discussing the ideas behind ML and covering a little ✨math & statistics✨🎉. As we journey further along, we'll collaborate & help one another with projects & other fun 🔥 stuff.

Automate the Boring Stuff With Python:   A friendly forum where we can ask questions, provide feedback & help each other with our coding journey. Explore our code & notes for each chapter here!