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Python For Data Science - 2018 | Become Data Scientist
Kevin Markham - Using pandas for Better (and Worse) Data Science - PyCon 2018
Christopher Fonnesbeck - Introduction to Statistical Modeling with Python - PyCon 2017
Jake VanderPlas - Exploratory Data Visualization with Vega, Vega-Lite, and Altair - PyCon 2018
UMAP Uniform Manifold Approximation and Projection for Dimension Reduction | SciPy 2018 |
SciPy Crash Course - Scientific Computing in Python
Optimizing Scientific Python with C++, CUDA, and Serverless Compute - Alex Zinovev (PyCon AU 2026)
Ned Batchelder - Big-O: How Code Slows as Data Grows - PyCon 2018
Your Pythonic Math Class of the __future__
Allen Downey - Introduction to Digital Signal Processing - PyCon 2018
Python-based scientific computing II
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Last Updated: September 20, 2026
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Speaker: Peter Farrell Topic: Learning Speaker: Christopher Fonnesbeck Nowadays, there are many ways of building data This tutorial introduces users to Speaker: Kevin Markham The pandas library is a powerful tool for multiple phases of the data "Speaker: Christopher Fonnesbeck This intermediate-level tutorial will provide students with hands-on experience applying ... Speaker: Jake VanderPlas Exploring a new dataset visually can provide quick intuition into the relationships within the data. This talk will present a new approach to dimension reduction called UMAP. UMAP is grounded in manifold learning and topology, ... Need some help with a project or some consulting? Contact me here: neuralnine.com/services The (Alex Zinovev) Moving computationally intensive Speaker: Ned Batchelder Big-O is a computer By Kirby Urner. Currently most K-12 Speaker: Allen Downey Spectral analysis is an important and useful technique in many areas of
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