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awesome-python-videos
Learn and watch python, machine learning, and data science videos from conferences (PyCon, PyData, SciPy, PyBay, EuroPython)
https://github.com/acharles7/awesome-python-videos
- Build Your Own Async (David Beazley)
- Structuring Your First Python Project
- Object Oriented Programming from scratch (four times)
- Modern Dictionaries
- Transforming Code into Beautiful, Idiomatic Python
- How to become a Data Scientist in 6 months
- High Performance Data Processing in Python
- Magic Wormhole- Simple Secure File Transfer
- PyCon
- PyCon 2020
- Object Oriented Programming from scratch (four times)
- Introduction to Decorators: Power Up Your Python Code
- Python Concurrency: from beginner to pro
- Migration from Python 2 to 3
- Natural Language Processing (NLP) in Python - From Zero to Hero
- Modern Python Developer's Toolkit
- Why is Python slow?
- A careful walk through probability distributions, using Python
- PyCon 2019
- Practical decorators
- Design Patterns in Python for the Untrained Eye
- Type hinting (and mypy)
- PEP 572: The Walrus Operator
- Thinking like a Panda: Everything you need to know to use pandas the right way
- PyCon 2018
- Python Oddities Explained
- Reinventing the Parser Generator
- Dataclasses: The code generator to end all code generators
- Type-checked Python in the real world
- PyCon 2017
- A Really Gentle Introduction to Asyncio
- PyCon 2016
- Thinking about Concurrency
- Refactoring Python: Why and how to restructure your code
- Magic Wormhole- Simple Secure File Transfer
- Type Hints
- Beyond PEP 8 -- Best practices for beautiful intelligible code
- Python Concurrency From the Ground Up
- Modules and Packages
- PyData
- Furious & Fast Python 7: Writing Fast Python Code
- Making Pandas Fly
- Pandas and friend
- PyData 2019
- Objectionable Content
- Customizing JupyterLab using extensions
- ADTK: An open-source Python toolkit for anomaly detection in...
- Machine Learning Crash Course
- AI pipelines powered by Jupyter notebooks
- Do You Want To Build A Forest?
- A gentle introduction to Pandas timeseries and Seaborn
- Stars, Planets, and Python
- A/B Testing in Python
- Dealing With Imbalanced Classes in Machine Learning
- I Just Inherited 50,000 Lines of Code! What Now? — A Practical Guide
- Applying Statistical Modeling & Machine Learning to Perform Time-Series Forecasting
- Winning with Simple, even Linear, Models
- More About Generators
- Unit Testing for Data Scientists
- Cleaning and Tidying Data in Pandas
- Train, Evaluate, Repeat: Building a Credit Card Fraud Detection System
- Using Simpson’s Paradox to Discover Interesting Patterns in
- High Performance Data Processing in Python
- Making Computation Easier with Cool Numpy Tricks
- Applied Data Science
- So you want to be a Python expert?
- Building Web-based Analysis & Simulation Platforms
- Top to down, left to right (Surprise talk)
- Advanced Metaphors in Coding with Python
- Time Series Forecasting using Statistical and Machine Learning Models
- A Worked Example of Using Neural Networks for Time Series Prediction
- Python Language
- Memory Management in Python - The Basics
- Design Principles
- Fizz Buzz in Tensorflow
- Learning scikit learn - An Introduction to Machine Learning in Python
- Design Principles
- How to become a Data Scientist in 6 months
- Python and Johnny Cash
- Does Code Quality Really Matter
- Machine Learning with scikit learn
- Learning Data Science Using Functional Python
- Deploying scikit learn Models in Production
- CPython Meanderings
- Generators Will Free Your Mind
- PyBay
- The Mental Game of Python
- Perceiving Python Programming Paradigms
- Patterns for Clean API Design
- What's Coming in 3 8 Assignment Expressions & More!
- Preventing, Finding, and Fixing Bugs On a Time Budget
- asyncio: what's next
- Logging and Testing and Debugging, Oh My!
- Keynote on Concurrency
- Being a Core Developer in Python
- Python Memory Model & Best Practices
- SciPy
- GPU-Accelerated Data Analytics in Python
- Learning from Evolving Data Streams
- Bayesian Statistics Made Simple
- Introduction to Python
- Introduction to Numerical Computing with NumPy - Leclerc
- Introduction to Matplotlib
- Introduction to Data Processing in Python with Pandas
- Image Analysis in Python with SciPy and Scikit Image - Iglesias
- Turning HPC Systems into Interactive Data Analysis Platforms
- Modern Time Series Analysis
- Visualize any Data Easily, from Notebooks to Dashboards
- Turn any Notebook into a Deployable Dashboard
- Productionalizing a Data Science Team
- Better and Faster Hyper Parameter Optimization with Dask
- Model Remodeling with Modern Deep Learning Frameworks
- Using a Stacking Model Ensemble Approach to Predict Rare Events
- EuroPython
- Writing faster Python
- Wait, IPython can do that?!
- Modern Dictionaries
- Learning From Games and Puzzles
- Docker for Data Science
- Natural Language Processing in Python
- Fun with TPUs
- TensorFlow, Deep Learning, and Modern Convolutional Neural Nets, Without a PhD
- Applying Statistical Modeling & Machine Learning to Perform Time-Series Forecasting
- Learning scikit learn - An Introduction to Machine Learning in Python
- Machine Learning with scikit learn
- Episode 1.1: Intro and building a ML framework
- Episode 1.2: Building an inference for the ML framework
- Episode 2: A Cross Validation Framework
- Episode 3: Handling Categorical Features in ML Problems
- Deploying scikit learn Models in Production
- contributing guidelines
- @charlespatel