Talk Python To Me
By Michael Kennedy (@mkennedy)
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Subscribers: 2719
Reviews: 4
Nov 7, 2018
one of my absolute favourite podcasts even though im almost non-skilled im python, always feel inspired listening to this podcast !
Morten
Oct 3, 2018
:)
Wilber H
Sep 19, 2018
I wish there was a Python that talks about teaching Python. For reinforcement purposes while driving. Don't get me wrong, conversations are great but some tracks catered to just teaching would be great.
Travis W.
Aug 31, 2018
Been listening to this podcast for over 6 months now and all I can say is that I'm continually pleased with every episode!
Description
Talk Python to Me is a weekly podcast hosted by developer and
entrepreneur Michael Kennedy. We dive deep into the popular packages
and software developers, data scientists, and incredible hobbyists doing
amazing things with Python. If you're new to Python, you'll quickly learn
the ins and outs of the community by hearing from the leaders. And if
you've been Pythoning for years, you'll learn about
your favorite packages and the hot new ones coming out of open source.
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#305 Python community at Python Discord
01:01:41
People often ask me how they can find a Python community to be part of. Maybe discussion forum or slack channel. This week, we look at one of the most active communities in Python Discord. It's Python, on a discord server. But it's more than that too.
You'll meet Leon Sandøy who, along with a team of folks, runs Python Discord. Links from the show Leon on Twitter: @lemonsaurus_rex Leon on the web: lemonsaur.us Leon on GitHub: github.com Python Discord: pythondiscord.com Python Discord's YouTube: youtube.com Python Discord on Twitter: @pythondiscord Python Discord on GitHub: github.com PEP 8 Song: youtube.com YouTube Live Stream version of this show: youtube.com Sponsors Linode Talk Python Training |
Mar 01, 2021 |
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#304 asyncio all the things with Omnilib
01:00:50
The relatively recent introduction of async and await as keywords in Python have spawned a whole area of high performance, highly scalable frameworks and supporting libraries. One such library that has great async building blocks is Omnilib.
On this episode, you'll meet John Reese. John is the creator of Omnilib, which includes packages such as aioitertools, aiomultiprocess, and aiosqlite. Join us as we async all the things. Links from the show Omnilib libraries and project: omnilib.dev awesome-asyncio: github.com unsync: asherman.io Live Youtube Stream: youtube.com Charities Power On: poweronlgbt.org The Trevor Project: thetrevorproject.org Sponsors Linode Talk Python Training |
Feb 21, 2021 |
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#303 Python for Astronomy with Dr. Becky
01:03:56
If you are involved in science or use computational tools in your work, you should be using code to solve your problem. On this episode, we have Dr. Becky Smethurst who's an astrophysicist at Oxford University. She uses Python to explore galaxies and black holes.
Learn how she's using Python to make new discoveries at the cutting edge of research and dive into a couple of her YouTube videos aimed at spreading scientific truth in an entertaining wrapper. Links from the show Dr. Becky on Twitter: @drbecky_ Dr. Becky's YouTube channel: youtube.com 5 ways I use code as an astrophysicist video: youtube.com Astrophysicist reacts to funny space MEMES video: youtube.com A day in the life of an Oxford University Astrophysicist: youtube.com Book: Space: 10 things you should know: amazon.com SpaceMemes Apple maps: image Otter space: image Eclipses: image Steals a cow: image Black holes: image YouTube live stream: youtube.com Sponsors Linode CloudEnv Talk Python Training |
Feb 12, 2021 |
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#302 The Data Engineering Landscape in 2021
01:04:33
I'm sure you're familiar with data science. But what about data engineering? Are these the same or how are they related?
Data engineering is dedicated to overcoming data-processing bottlenecks, data cleanup, data flow and data-handling problems for applications that utilize lots of data. On this episode, we welcome back Tobias Macey to give us the 30,000 ft view of the data engineering landscape in 2021. Links from the show Live Stream Recordings: YouTube: youtube.com Tobias Macey: boundlessnotions.com Podcast.__init__: pythonpodcast.com Data Engineering podcast: dataengineeringpodcast.com Designing Data-Intensive Applications Book: amazon.com wally: github.com lakeFS: lakefs.io A Beginner’s Guide to Data Engineering: medium.com Apache Airflow: airflow.apache.org Dagster: dagster.io Prefect: prefect.io #68 Crossing the streams with Podcast.__init__: talkpython.fm/68 dbt: getdbt.com Great Expectations: github.com Dask: dask.org Meltano: meltano.com Languages trends on StackOverflow: insights.stackoverflow.com DVC: dvc.org Pandas: pandas.pydata.org Sponsors Datadog Retool Talk Python Training |
Feb 04, 2021 |
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#301 Deploying and running Django web apps in 2021
01:08:34
Have you been learning Django and now want to get your site online? Not sure the best way to host it or the trade offs between the various options? Maybe you want to make sure your Django site is secure. On this episode, I'm joined by two Django experts Will Vincent and Carlton Gibson to talk about deploying and running Django in production along with recent updates in Django 3.2 and beyond.
Links from the show Guests Will Vincent: wsvincent.com Carlton Gibson: @carltongibson Watch the live stream: youtube.com Give me back my monolith: craigkerstiens.com Carlton’s Button hosting platform: btn.dev Django Software Foundation: djangoproject.com Django News newsletter: django-news.com Deployment Checklist: djangoproject.com Environs 3rd party package for environment variables: github.com Django Static Files & Templates: learndjango.com Learn Django: LearnDjango.com Configuring uWSGI for Production Deployment @ Bloomberg: techatbloomberg.com Sponsors Square Linode Talk Python Training |
Jan 28, 2021 |
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#300 Building a data science startup (panel)
01:06:22
You've heard that software developers and startups go hand-in-hand. But what about data scientists? Of course they! But how do you turn your data science skill set into a data science business skill set? What are some of the areas ripe for launching such a business into?
On this episode, I welcome back 4 prior guests who have all walked their own version of this path and are currently running successful Python-based Data Science startups: * Ines Montani from Explosion AI * Matthew Rocklin from Coiled * Jonathon Morgan from Yonder AI * William Stein from Cocalc Links from the show Ines Montani Twitter: @_inesmontani Explosion AI: explosion.ai Matthew Rocklin Twitter: @mrocklin Coiled: coiled.io Jobs @ Coiled: jobs.lever.co/coiled Jonathon Morgan Twitter: @jonathonmorgan Yonder AI: yonder-ai.com William Stein Twitter: @wstein389 CoCalc: cocalc.com Talk Python Live Streams: talkpython.fm/youtube Sentry Promo Code: TALKPYTHON2021 Sponsors Sentry Error Monitoring, Code TALKPYTHON Linode Talk Python Training |
Jan 22, 2021 |
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#299 Personal search engine with datasette and dogsheep
01:01:42
In this episode, we'll be discussing two powerful tools for data reporting and exploration: Datasette and Dogsheep.
Datasette helps people take data of any shape or size, analyze and explore it, and publish it as an interactive website and accompanying API. Dogsheep is a collection of tools for personal analytics using SQLite and Datasette. Imagine a unified search engine for everything personal in your life such as twitter, photos, google docs, todoist, goodreads, and more, all in once place and outside of cloud companies. On this episode we talk with Simon Willison who created both of these projects. He's also one of the co-creators of Django and we'll discuss some early Django history! Links from the show Datasette: datasette.io Dogsheep: dogsheep.github.io Datasheet newsletter: datasette.substack.com Video: Build your own data warehouse for personal analytics with SQLite and Datasette: youtube.com Examples List: github.com Personal data warehouses: github.com Global power plants: datasettes.com SF data: datasettes.com FiveThirtyEight: fivethirtyeight.datasettes.com Lahman’s Baseball Database: baseballdb.lawlesst.net Live demo of current main: datasette.io Sponsors Linode Talk Python Training |
Jan 17, 2021 |
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#298 Building ML teams and finding ML jobs
56:10
Are you building or running an internal machine learning team? How about looking for a new ML position? On this episode, I talk with Chip Huyen from Snorkel AI about building ML teams, finding ML positions, and teach ML at Stanford.
Links from the show Chip on Twitter: @chipro Snorkel AI: snorkel.ai Chip's Book Preview: twitter.com handcalcs project: github.com IBM Buzzword Bingo: youtube.com Sponsors Datadog Linode Talk Python Training |
Jan 11, 2021 |
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#297 Python year in review (2020 edition)
01:10:23
2020 will be one for the history books, won't it? I've put together a great group to look back on 2020 - from the Python perspective.
Join me along with Cecil Phillip, Ines Montani, Jay Miller, Paul Everitt, Reuven Lerner, Matt Harrison, and Brian Okken for a light-hearted and fun look back on the major Python events of 2020. Links from the show Video version of this episode: youtube.com Guests Cecil Phillip: @cecilphillip Ines Montani: @_inesmontani Jay Miller: @kjaymiller Paul Everitt: @paulweveritt Reuven Lerner: @reuvenmlerner Matt Harrison: @__mharrison__ Brian Okken: @brianokken Sponsors Talk Python Training |
Dec 28, 2020 |
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#296 Python in F1 racing
01:05:14
Quick: Name the 3 most advanced engineering organizations you can think of? Maybe an aerospace company such as SpaceX or Boeing come to mind. Maybe you thought of CERN and the LHC. But in terms of bespoke engineering capabilities, you should certainly put the F1 racing teams on your list.
These organizations appear as 20-30 people on a race day shown on TV. But in fact, the number of people back at the home base doing the engineering work can be over 500 employees. Almost every tiny part you see on these cars as well as the tools to maintain them are custom-built. The engineering problems solved are immense. Would it surprise you to know that Python is playing a major role here? On this episode, you'll meet Joe Borg who help pioneer Python's adoption at several F1 teams. Links from the show Joe's website: josephb.org Joe on Twitter: @joedborg Racing Point F1 team: racingpointf1.com Scuderia Alpha Tauri F1 team: scuderiaalphatauri.com MicroK8s: microk8s.io Charmed Kubernetes: ubuntu.com/kubernetes Sponsors Talk Python Training Linode |
Dec 23, 2020 |
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#295 GIS + Python
57:00
Geography is the study of places and the relationships between people and their environments. Often we think of maps, but maps are static. GIS gets interesting when you realize that we're studying and visualizing data flowing through these locations and communities.
In this episode, you'll meet Silas Toms. He's an author of several Python GIS books and the host of The Mappist Hour podcast. Are you ready to dive into GIS with Python? Links from the show Silas on twitter Twitter: @loki_president Silas' Books: Mastering Geospatial Analysis with Python: Explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter: amazon.com ArcPy and ArcGIS – Geospatial Analysis with Python: amazon.com ArcPy and ArcGIS - Second Edition: Automating ArcGIS for Desktop and ArcGIS Online with Python: amazon.com The Mappyist Hour podcast: themappyisthour.com Packages GeoAlchemy ORM: geoalchemy-2.readthedocs.io Leaflet.js: leafletjs.com Mapbox GL: mapbox.com Deck GL: deck.gl Sponsors Talk Python Training Linode |
Dec 18, 2020 |
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#294 oso authorizes Python
51:27
When we think about accounts and security, we often think about identity (logging in and proving who you are). But for many applications, especially internal apps at large organizations, that's just step one. The next step is what can you do and what can you not do.
In this episode, you'll learn about a new library called oso. It's a declarative way to create policy code that maps to your mental model for who is allowed to do what in your system. We have two guests, Graham Neray and Sam Scott from the oso project to tell us all about it. Links from the show Oso on twitter: @osoHQ Graham on twitter: @grahamneray Sam on twitter: @samososos Oso: osohq.com Django docs: docs.osohq.com Flask docs: docs.osohq.com Python library docs: docs.osohq.com Source code: github.com/osohq Debugger docs: docs.osohq.com Polar Adventure: A text-based adventure game written in Polar: osohq.com Adding authorization to your Flask app with oso: osohq.com Building a Django app with data access controls: osohq.com Django Queryset filters from oso policies: osohq.com Recent episode on authentication over at Talk Python: talkpython.fm/292 MongoDB most wanted DB: insights.stackoverflow.com Talk Python [pro edition]: talkpython.fm/pro FastAPI course: talkpython.fm/fastapi Sponsors Talk Python Training |
Dec 07, 2020 |
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#293 Learning how to learn as a developer
01:00:07
As software developers, we live in a world of uncertainty and flux. Do you need to build a new web app? Well maybe using Django makes the most sense if you've been doing it for a long time. There is Flask, but it's more mix and match being a microframework. But you've also heard that async and await are game changers and FastAPI might be the right choice.
Whatever it is you're building, there is constant pressure to stay on top of a moving target. Learning is not something you do in school then get a job as a developer. No, it a constant and critical part of your career. That's why we all need to be good, very good, at it. Matt Harrison is back on Talk Python to talk to us about some tips, tricks, and even science about learning as software developers. Links from the show Matt on Twitter: @__mharrison__ Matt's Learning Course (use code TALKPYTHON20 for 20% off): mattharrison.podia.com Friends of the show: talkpython.fm/friends-of-the-show Streamlit: streamlit.io Jupyter LSP: github.com/krassowski/jupyterlab-lsp Sponsors Brilliant Linode Talk Python Training |
Dec 01, 2020 |
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#292 Pythonic identity (auth in Python ecosystem)
01:05:01
So you're excited about that next app you're about to build. You can visualize the APIs with the smooth scalability taking to the mobile apps. You can see how, finally, this time, you'll get deployment right and it'll be pure continuous delivery out of GitHub with zero downtime.
What you're probably not dreaming about is writing yet another password reset form and integrating mail capabilities just for this purpose. Or how you'll securely store user accounts the right way this time. Don't worry, we got you covered. Our guests, Christos Matskas and John Patrick Dandison are here to cover a bunch of different libraries and techniques we can use for adding identity to our Python applications. Links from the show Christos on Twitter: @christosmatskas John Patrick Dandison on Twitter: @azureandchill shhgit live: shhgit.com Twitch channel for Christos and JP: twitch.tv/425show Passlib & Folding: passlib.readthedocs.io Microsoft Authentication Library: github.com/AzureAD authlib - JavaScript Object Signing and Encryption draft implementation: github.com django-allauth - Authentication app for Django that "just works": github.com django-oauth-toolkit - OAuth 2 goodies for Django: github.com python-oauth2 - A fully tested, abstract interface to creating OAuth clients and servers: github.com python-social-auth - An easy-to-setup social authentication mechanism: github.com Sponsors Talk Python Training Linode |
Nov 26, 2020 |
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#291 Operational Resilience with Pyomo
59:36
Do you have a scientific system that needs optimization or solving? Our guest, on this episode, Clark Petri is here to tell us all about pyomo. This is a library that can solve all sorts of cool problems, linear programming, nonlinear equations, and many other things you can throw at it.
We're gonna solve a really fun diet problem: What is the most nutritious meal that you can eat for the least amount of money? The answer might surprise you a little bit! It's going to be a lot of fun. So listen in to hear about how Clark has used pyomo to do his work and how you might use it in yours. Links from the show Pyomo: pyomo.org Clark on Twitter: @clarkpetri Center for Infrastructure Defense: nps.edu Thesis: apps.dtic.mil I’m not alone in my work post: morenuance.com handcalcs package: github.com Diet optimization problem: nbviewer.jupyter.org Talk Python [Pro Edition]: talkpython.fm/pro Black Friday at Talk Python: talkpython.fm/blackfriday Sponsors Talk Python Training Linode |
Nov 22, 2020 |
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#290 Side Hustles for Data Scientists
01:08:04
Are you a data scientist looking to branch out on your own and start something new? Maybe you're just looking for a way to work with those exciting libraries that aren't yet in play at the day job. Rather than putting everything on the line, quitting your job, and hoping things work out, maybe you should start with a side-hustle.
On this episode, you'll meet Keith McCormick, a data scientist who has many irons in the fire and he's here to tell us about different types of side hustles and why you may want to try or avoid one. Links from the show Keith on Twitter: @kmccormickblog Keith on LinkedIn: linkedin.com Keith's courses: linkedin.com Side Hustle Strategies for Data Science and Analytics Experts course: linkedin.com/learning Talk Python's Excel to Python course: talkpython.fm/excel Sponsors Linode Talk Python Training |
Nov 13, 2020 |
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#289 Discovering exoplanets with Python
47:26
When I saw the headline "Machine learning algorithm confirms 50 new exoplanets in historic first" I knew the Python angle of this story had to be told! And that's how this episode was born. Join David Armstrong and Jev Gamper as they tell us how they use Python and machine learning to discover not 1, but 50 new exoplanets in pre-existing Keplar satellite data.
Links from the show Jev Gamper on Twitter: @brutforcimag Machine learning algorithm confirms 50 new exoplanets in historic first article: techrepublic.com Sponsors Brilliant Talk Python Training |
Nov 09, 2020 |
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#288 10 tips to move from Excel to Python
01:03:23
Excel is one of the most used and most empowering piece of software out there. But that doesn't make it a good fit for every data processing need. And when you outgrow Excel, a really good option for a next step is Python and the data science tech stack: Pandas, Jupyter, and friends.
Chris Moffitt is back on Talk Python to give us concrete tips and tricks for moving from Excel to Python! Links from the show Chris on Twitter: @chris1610 Practical Business Python: pbpython.com Escaping Excel Hell with Python and Pandas Episode 200: talkpython.fm SideTable package: pbpython.com Learn more and go deeper Move from Excel to Python with Pandas Course: training.talkpython.fm Excel to Python webcast: crowdcast.io Sponsors Voyager game Linode Talk Python Training |
Oct 31, 2020 |
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#287 Testing without dependencies, mocking in Python
01:03:29
We know our unit tests should be relatively independent from other parts of the system. For example, running a test shouldn't generally call a credit card possessing API and talk to a database when your goal is just to test the argument validation.
And yet, your method does all three of those and more. What do you do? Some languages use elaborate dependency passing frameworks that go under the banner of inversion of control (IoC) and dependency injections (DI). In Python, the most common fix is to temporarily redefine what those two functions do using patching and mocking. On this episode, we welcome back Anna-Lena Pokes to talk us through the whole spectrum of test doubles, dummies, mocks, and more. Links from the show Anna-Lena's personal site: alpopkes.com 100 Days of Code episode: talkpython.fm/186 Anna-Lena on Github: github.com PyCon talk from Lisa Road (2018) - “Demystifying the patch function”: youtube.com PyCon talk from Edwin Jung (2019) - Mocking and Patching Pitfalls: youtube.com Keynote talk “Finding Magic in Python” (about magical universe project): youtube.com Blog post about mocking in Python: alpopkes.com Stackoverflow post on difference between stubs and mocks: stackoverflow.com Freezegun project: github.com KI Macht Schule (AI goes to school): ki-macht-schule.de Code Combat: codecombat.com PDB++: github.com Sponsors Linode Monday.com Talk Python Training |
Oct 21, 2020 |
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#286 Python and ML at NASA Jet Propulsion Laboratory (JPL)
01:07:32
NASA's Jet Propulsion Laboratory (JPL)'s primary function is the construction and operation of planetary robotic spacecraft, though it also conducts Earth-orbit and astronomy missions. It is also responsible for operating NASA's Deep Space Network.
On this episode, you'll meet Chris Mattman. He's the Division Manager for the Artificial Intelligence, Analytics and Innovation at NASA JPL and he's JPL's first Principal Scientist in the area of Data Science. We cover a wide range of topics, and dive into how Python and open-source are growing in the space exploration field. And he answers the question of whether he thinks we'll have Python running on robots and rovers in space. Links from the show Chris on Twitter: @chrismattmann Chris at JPL: jpl.nasa.gov Nature: A vision for data science: nature.com Open source at JPL: github.com Apache Nutch: nutch.apache.org 7 Minutes of Terror: The Challenges of Getting to Mars: youtube.com tqdm package: pypi.org Panama Papers: wikipedia.org Sponsors Linode Monday.com Talk Python Training |
Oct 16, 2020 |
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#285 Dask as a Platform Service with Coiled
01:11:04
If you're into data science, you've probably heard about Dask. It's a package that feels like familiar APIs such as Numpy, Pandas, and Scikit-Learn. Yet it can scale that computation across CPU cores on your local machine all the way to distributed grid-based computing in large clusters.
While powerful, this may take some serious setup to execute in its full glory. That's why Matthew Rocklin has teamed up with Hugo Bowne-Anderson and others to launch a business to help Python loving data scientists run Dask workloads in the cloud. And they are here to tell us about they open-source foundation business. And they must be on to something, between recording and releasing this episode, they raised $5M in VC funding. Links from the show Hugo on Twitter: @hugobowne Matthew on Twitter: @mrocklin Coiled: coiled.io Coiled raised $5M in Sept: twitter.com A brief history of dask article: coiled.io/blog Coiled: Dask for Everyone, Everywhere: medium.com The incredible growth of python: stackoverflow.blog Growth updated (SO Trends current): insights.stackoverflow.com Coiled Youtube channel: youtube.com Snorkel package: pypi.org Sponsors Brilliant Monday.com Talk Python Training |
Oct 09, 2020 |
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#284 Modern and fast APIs with FastAPI
01:06:06
As Python 3 has eclipsed the old constrains of Python 2 and web frameworks that adopted them, we have seen a big jump in new frameworks appearing on the scene taking full advantage of things like type hints, async and await, and more.
No framework has done this more successfully than FastAPI recently. That's why we are here with the creator of FastAPI, Sebastián Ramírez to dive into this exciting new Python web framework. Links from the show Sebastian: @tiangolo FastAPI: fastapi.tiangolo.com FastAPI: One of the fastest Python frameworks available: fastapi.tiangolo.com FastAPI for Flask Users: amitness.com FastAPI Docker image: https://github.com/tiangolo/uvicorn-gunicorn-fastapi-docker ujson: github.com uvicorn: uvicorn.org Traffic server: docs.traefik.io Starlette: starlette.io Pydantic: pydantic-docs.helpmanual.io Sponsors Linode Talk Python Training |
Oct 04, 2020 |
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#283 Web scraping, the 2020 edition
48:34
Web scraping is pulling the HTML of a website down and parsing useful data out of it. The use-cases for this type of functionality are endless. Have a bunch of data on governmental sites that are only listed online in HTML without a download? There's an API for that! Do you want to keep abreast of what your competitors are featuring on their site? There's an API for that. Need alerts for changes on a website, for example enrollment is now open at your college and you want to be first to get in and avoid the 8am Monday morning course slot? There's an API for that.
That API is screen scraping and Attila Tóth from ScrapingHub is here to tell us all about it. Links from the show Attila Tóth on LinkedIn: linkedin.com Scrapy project: scrapy.org Scrapinghub on Twitter: @scrapinghub Scrapinghub: scrapinghub.com cookiecutter template for Scrapy projects: github.com Splash: headless browser designed specifically for web scraping: scrapinghub.com/splash Awesome Web Scraping list: github.com Talk Python episode 50 on web scraping: talkpython.fm How Web Scraping is Revealing Lobbying and Corruption in Peru: blog.scrapinghub.com Web Data Extraction Summit event: extractsummit.io Sponsors Talk Python Training Linode |
Sep 23, 2020 |
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#282 pre-commit framework
59:33
Git hook scripts are useful for identifying simple issues before committing your code. Hooks run on every commit to automatically point out issues in code such as trailing whitespace and debug statements. By pointing these issues out before code review, this allows a code reviewer to focus on the architecture of a change while not wasting time with trivial style nitpicks.
As we created more libraries and projects we recognized that sharing our pre-commit hooks across projects is painful. That's why I'm happy to welcome Anthony Sottile to the show to discuss pre-commit, a framework for managing and maintaining multi-language pre-commit hooks. Links from the show Anthony at Twitter: @codewithanthony pre-commit: pre-commit.com pre-commit continuous integration: pre-commit.ci pre-commit hooks: pre-commit.com/hooks.html pre-commit on GitHub: github.com shhgit secret discovery project: github.com babi editor: github.com Twitch stream: twitch.tv Anthony on GitHub: github.com Sponsors Talk Python Training Linode |
Sep 17, 2020 |
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#281 Python in Car Racing
01:00:14
I love to bring you stories of Python being used in amazing places outside the traditional tech silos of pure web development and data science.
On this episode, you'll meet Robert "Kane" Replogle, who works on the simulation and test software at Richard Childress Racing. The NASCAR team that just finished #1 and 2 in at the Texas Motor Speedway. You'll hear how Python is allowing them to model car behavior, air flow, and more much faster than others using outdated tools.  Watch the hot lap around Brands Hatch Links from the show Kane on LinkedIn: linkedin.com Kane on Twitter: @ReplogleRk Richard Childress Racing: rcrracing.com Windshear, the 180 mph tunnel: windshearinc.com NASCAR: nascar.com blackcellmagic package: pypi.org/project/blackcellmagic StreamLit: streamlit.io Sponsors Linode SonarQube linting tools Talk Python Training |
Sep 09, 2020 |
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#280 Python and AI in Journalism
55:51
If there has ever been a time in history that journalism is needed to shine a light on what's happening in the world, it's now. Would it surprise you to hear that Python and machine learning are playing an increasingly important role in discovering and bringing us the news? On this episode, you'll meet Carolyn Stansky, a journalist and developer who's been researching this intersection.
Links from the show Carolyn on Twitter: @carolstran Carolyn on LinkedIn: linkedin.com Carolyn's site: workwithcarolyn.com Carolyn's talk: How AI is enhancing journalism: vimeo.com Examples of AI / automation in use Quakebot: bit.ly/quakebot-code LA Homicide Tracker: homicide.latimes.com reportermate: github.com Buzzfeed Finding and tracking secret spy planes: bit.ly/buzzfeed-spy-planes NY Times comment moderation: bit.ly/nyt-comments Al Jazzira: Drones in warzones: bit.ly/fmls-keynote Tools Qz.ai - Quartz AI Studio, focused on helping smaller papers and journalists: qz.ai Facets: github.io Google News Initiative: bit.ly/google-ni Newspaper3k Package: newspaper.readthedocs.io FiveThirtyEight: fivethirtyeight.com Google News and Australia fight: bbc.com Twitter thread on American news overwhelming other countries: twitter.com Sponsors Brilliant Talk Python Training |
Sep 05, 2020 |