hilary_mason_data hilary_mason_data-2011 hilary_mason_data-2011-53 knowledge-graph by maker-knowledge-mining

53 hilary mason data-2011-03-11-Conference: PyCon 2011 Keynote!


meta infos for this blog

Source: html

Introduction: Conference: PyCon 2011 Keynote! Posted: March 11, 2011 | Author: hilary | Filed under: blog , Presentations | Tags: conference , conferences , pycon , python | 1 Comment » I gave the opening keynote this morning at PyCon . The one thing that everyone in the room at PyCon has in common is that we all love to code. I used that as the central theme of the talk, spoke about the constructs that give us joy, the history of some of our favorite patterns (they date as far back as the 60s!) and proposed that we think about the way we’ll compute fifty years into the future. There’s also a bit of fun data hacking, of course. PyCon 2011 Keynote View more presentations from Hilary Mason . Enjoy the slides. The video is up! Please let me know here or on Twitter if you have any questions or comments.


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 Posted: March 11, 2011 | Author: hilary | Filed under: blog , Presentations | Tags: conference , conferences , pycon , python | 1 Comment » I gave the opening keynote this morning at PyCon . [sent-2, score-1.708]

2 The one thing that everyone in the room at PyCon has in common is that we all love to code. [sent-3, score-0.471]

3 I used that as the central theme of the talk, spoke about the constructs that give us joy, the history of some of our favorite patterns (they date as far back as the 60s! [sent-4, score-1.185]

4 ) and proposed that we think about the way we’ll compute fifty years into the future. [sent-5, score-0.506]

5 There’s also a bit of fun data hacking, of course. [sent-6, score-0.227]

6 PyCon 2011 Keynote View more presentations from Hilary Mason . [sent-7, score-0.139]

7 Please let me know here or on Twitter if you have any questions or comments. [sent-10, score-0.176]


similar blogs computed by tfidf model

tfidf for this blog:

wordName wordTfidf (topN-words)

[('pycon', 0.68), ('keynote', 0.331), ('proposed', 0.151), ('theme', 0.151), ('compute', 0.151), ('history', 0.151), ('presentations', 0.139), ('conference', 0.139), ('opening', 0.136), ('patterns', 0.136), ('date', 0.125), ('spoke', 0.125), ('enjoy', 0.117), ('conferences', 0.117), ('hacking', 0.11), ('morning', 0.11), ('room', 0.11), ('gave', 0.1), ('years', 0.1), ('used', 0.095), ('common', 0.095), ('back', 0.095), ('python', 0.095), ('everyone', 0.091), ('view', 0.091), ('favorite', 0.091), ('bit', 0.088), ('far', 0.088), ('video', 0.088), ('thing', 0.076), ('march', 0.071), ('give', 0.069), ('love', 0.067), ('questions', 0.067), ('let', 0.065), ('twitter', 0.062), ('fun', 0.062), ('please', 0.06), ('us', 0.059), ('think', 0.052), ('way', 0.052), ('ll', 0.047), ('talk', 0.047), ('also', 0.044), ('know', 0.044), ('comment', 0.039), ('data', 0.033), ('one', 0.032), ('mason', 0.018), ('comments', 0.012)]

similar blogs list:

simIndex simValue blogId blogTitle

same-blog 1 0.99999994 53 hilary mason data-2011-03-11-Conference: PyCon 2011 Keynote!

Introduction: Conference: PyCon 2011 Keynote! Posted: March 11, 2011 | Author: hilary | Filed under: blog , Presentations | Tags: conference , conferences , pycon , python | 1 Comment » I gave the opening keynote this morning at PyCon . The one thing that everyone in the room at PyCon has in common is that we all love to code. I used that as the central theme of the talk, spoke about the constructs that give us joy, the history of some of our favorite patterns (they date as far back as the 60s!) and proposed that we think about the way we’ll compute fifty years into the future. There’s also a bit of fun data hacking, of course. PyCon 2011 Keynote View more presentations from Hilary Mason . Enjoy the slides. The video is up! Please let me know here or on Twitter if you have any questions or comments.

2 0.14786716 49 hilary mason data-2010-11-10-Machine Learning: A Love Story

Introduction: Machine Learning: A Love Story Posted: November 10, 2010 | Author: hilary | Filed under: academics , blog , Presentations | Tags: conferences , machinelearning , presentations , video | 27 Comments » The video from my keynote at Strange Loop 2010 is up! You can watch the video here: Machine Learning: A Love Story The original abstract: Machine learning has come a long way in recent years — from a long-marginalized field so old it still has the word “machine” in the name, to the last, best hope for making sense of our massive flows of data. The art of ‘data science’ is asking the right questions; the answers are generally trivial or impossible. This talk will focus more on questions than on answers. I’ll give a brief history of the field with a focus on the fundamental math and algorithmic tools that we use to address these kinds of problems, then walk through several descriptive and predictive scenarios. Finally, I’ll show one example syst

3 0.1265687 62 hilary mason data-2011-09-25-Conference: Strata NY 2011

Introduction: Conference: Strata NY 2011 Posted: September 25, 2011 | Author: Hilary Mason | Filed under: Presentations | Tags: conference , keynote , presentations , strataconf , stratany | 1 Comment Âť The first Strata Conference in New York just wound up. It was a five day expo of business, data, and tech, and brought a ton of great people in the data community to New York. Thanks so much to Edd and Alistair and everyone whose hard work made this possible! My talk, Short URLs, Big Data: Learning in Realtime is already online: And the slides are up on Slideshare: Strata NY Sep 2011: Big Data, Short URLs: Learning in Realtime View more presentations from Hilary Mason

4 0.1113137 93 hilary mason data-2013-03-01-Speaking: Pick a Vague and Specific Title for Your Talk

Introduction: Speaking: Pick a Vague and Specific Title for Your Talk Posted: March 1, 2013 | Author: Hilary Mason | Filed under: speaking | Tags: presentations , speaking , title | Leave a comment » Your title should be both vague and specific . First, vague . You generally have to commit to give a talk months in advance of the actual event. You do not, however, generally have a talk written several months ahead of the actual event. You may also have a particular talk accepted, and then arrive at the conference and realize that what you had planned isn’t ideal for that audience. A vague title offers you a lot of flexibility in altering the content of your talk as conditions change without betraying the expectations of the audience based on the materials published earlier. And then, specific . If your title is too vague (“Stuff and Junk”) people won’t be excited for your talk, and you’ll lack an audience entirely or won’t make it through the CFP process at all. Be s

5 0.10654092 31 hilary mason data-2009-08-12-My NYC Python Meetup Presentation: Practical Data Analysis in Python

Introduction: My NYC Python Meetup Presentation: Practical Data Analysis in Python Posted: August 12, 2009 | Author: hilary | Filed under: blog | Tags: data , data analysis , nltk , presentations , python , spam , twitter | Leave a comment » I gave a talk at the NYC Python Meetup on July 29 on Practical Data Analysis in Python . I tend to use my slides for visual representations of the concepts I’m discussing, so there’s a lot of content that was in the presentation that you unfortunately won’t see here. The talk starts with the immense opportunities for knowledge derived from data. I spent some time showing data systems ‘in the wild’ along with the appropriate algorithmic vocabulary (for example, amazon.com ‘s ‘books you might like’ feature is a recommender system ). Once we can describe the problems properly, we can look for tools, and Python has many! Finally, in the fun part of the presentation, I demoed working code that uses NLTK to build a Twitter sp

6 0.10258178 44 hilary mason data-2010-06-24-Conference: Web2 Expo SF

7 0.099650607 54 hilary mason data-2011-03-18-Be Ballsy.

8 0.093966782 57 hilary mason data-2011-05-21-An Introduction to Machine Learning with Web Data is now available!

9 0.088618815 72 hilary mason data-2012-03-17-Short URLs, Big Fun: I spoke at dropbox!

10 0.078822583 30 hilary mason data-2009-06-01-My Barcamp Presentation: Have Data? What Now?!

11 0.076323129 81 hilary mason data-2013-01-03-Interview Questions for Data Scientists

12 0.064658329 94 hilary mason data-2013-03-08-Speaking: Title Slides + Twitter = You Win

13 0.061678469 76 hilary mason data-2012-08-28-How do you prioritize research?

14 0.058941625 51 hilary mason data-2011-02-11-Interview on Silicon Angle TV

15 0.057706837 73 hilary mason data-2012-07-04-Devs Love Bacon: Everything you need to know about Machine Learning in 30 minutes or less

16 0.055996273 103 hilary mason data-2013-06-04-Lucene Revolution Keynote: Search is Not a Solved Problem

17 0.052242428 38 hilary mason data-2009-12-24-IgniteNYC: The video!

18 0.05088811 40 hilary mason data-2010-02-16-Conference: Search and Social Media 2010

19 0.049427558 114 hilary mason data-2013-12-18-Using Twitter’s Lead-Gen Card to Recruit Beta Testers

20 0.04815805 37 hilary mason data-2009-11-25-IgniteNYC: How to Replace Yourself with a Very Small Shell Script


similar blogs computed by lsi model

lsi for this blog:

topicId topicWeight

[(0, -0.202), (1, -0.035), (2, 0.118), (3, -0.08), (4, -0.165), (5, -0.127), (6, -0.067), (7, 0.084), (8, 0.049), (9, 0.102), (10, 0.067), (11, 0.132), (12, 0.105), (13, 0.059), (14, 0.041), (15, -0.052), (16, -0.023), (17, 0.09), (18, 0.02), (19, -0.051), (20, -0.053), (21, -0.008), (22, -0.151), (23, -0.049), (24, 0.214), (25, 0.091), (26, -0.007), (27, 0.031), (28, 0.137), (29, -0.048), (30, -0.037), (31, -0.095), (32, 0.009), (33, -0.305), (34, 0.003), (35, 0.064), (36, 0.033), (37, -0.106), (38, 0.037), (39, 0.218), (40, -0.125), (41, 0.113), (42, 0.001), (43, -0.025), (44, 0.056), (45, -0.133), (46, -0.098), (47, 0.01), (48, 0.053), (49, -0.181)]

similar blogs list:

simIndex simValue blogId blogTitle

same-blog 1 0.98582667 53 hilary mason data-2011-03-11-Conference: PyCon 2011 Keynote!

Introduction: Conference: PyCon 2011 Keynote! Posted: March 11, 2011 | Author: hilary | Filed under: blog , Presentations | Tags: conference , conferences , pycon , python | 1 Comment » I gave the opening keynote this morning at PyCon . The one thing that everyone in the room at PyCon has in common is that we all love to code. I used that as the central theme of the talk, spoke about the constructs that give us joy, the history of some of our favorite patterns (they date as far back as the 60s!) and proposed that we think about the way we’ll compute fifty years into the future. There’s also a bit of fun data hacking, of course. PyCon 2011 Keynote View more presentations from Hilary Mason . Enjoy the slides. The video is up! Please let me know here or on Twitter if you have any questions or comments.

2 0.42128882 54 hilary mason data-2011-03-18-Be Ballsy.

Introduction: Be Ballsy. Posted: March 18, 2011 | Author: Hilary Mason | Filed under: blog | 9 Comments » The things that are hardest to make yourself do are often the ones that end up being the most rewarding. (By rewarding I mean they lead to the kinds of experiences where you learn something new, get to meet amazing people, and generally have opportunities to do things you never would have imagined doing before. Rewarding does not only mean money.) I was thinking about this at PyCon, after someone asked me how it felt, as a woman, to get up and give a technical talk to approximately 1,400 men. Five years ago I couldn’t have imagined myself doing something like that, but a series of small chances, risks, and experiences have led me here. And it was a ton of fun! I thought about this again when Bryce sent me a link to this post . OATV is hiring an analyst, and they haven’t received applications from women. The OATV team is a wonderful, smart, and energetic group of peop

3 0.39353946 49 hilary mason data-2010-11-10-Machine Learning: A Love Story

Introduction: Machine Learning: A Love Story Posted: November 10, 2010 | Author: hilary | Filed under: academics , blog , Presentations | Tags: conferences , machinelearning , presentations , video | 27 Comments » The video from my keynote at Strange Loop 2010 is up! You can watch the video here: Machine Learning: A Love Story The original abstract: Machine learning has come a long way in recent years — from a long-marginalized field so old it still has the word “machine” in the name, to the last, best hope for making sense of our massive flows of data. The art of ‘data science’ is asking the right questions; the answers are generally trivial or impossible. This talk will focus more on questions than on answers. I’ll give a brief history of the field with a focus on the fundamental math and algorithmic tools that we use to address these kinds of problems, then walk through several descriptive and predictive scenarios. Finally, I’ll show one example syst

4 0.38143525 93 hilary mason data-2013-03-01-Speaking: Pick a Vague and Specific Title for Your Talk

Introduction: Speaking: Pick a Vague and Specific Title for Your Talk Posted: March 1, 2013 | Author: Hilary Mason | Filed under: speaking | Tags: presentations , speaking , title | Leave a comment » Your title should be both vague and specific . First, vague . You generally have to commit to give a talk months in advance of the actual event. You do not, however, generally have a talk written several months ahead of the actual event. You may also have a particular talk accepted, and then arrive at the conference and realize that what you had planned isn’t ideal for that audience. A vague title offers you a lot of flexibility in altering the content of your talk as conditions change without betraying the expectations of the audience based on the materials published earlier. And then, specific . If your title is too vague (“Stuff and Junk”) people won’t be excited for your talk, and you’ll lack an audience entirely or won’t make it through the CFP process at all. Be s

5 0.34101799 62 hilary mason data-2011-09-25-Conference: Strata NY 2011

Introduction: Conference: Strata NY 2011 Posted: September 25, 2011 | Author: Hilary Mason | Filed under: Presentations | Tags: conference , keynote , presentations , strataconf , stratany | 1 Comment Âť The first Strata Conference in New York just wound up. It was a five day expo of business, data, and tech, and brought a ton of great people in the data community to New York. Thanks so much to Edd and Alistair and everyone whose hard work made this possible! My talk, Short URLs, Big Data: Learning in Realtime is already online: And the slides are up on Slideshare: Strata NY Sep 2011: Big Data, Short URLs: Learning in Realtime View more presentations from Hilary Mason

6 0.3379733 31 hilary mason data-2009-08-12-My NYC Python Meetup Presentation: Practical Data Analysis in Python

7 0.33320293 44 hilary mason data-2010-06-24-Conference: Web2 Expo SF

8 0.31940776 30 hilary mason data-2009-06-01-My Barcamp Presentation: Have Data? What Now?!

9 0.31389952 72 hilary mason data-2012-03-17-Short URLs, Big Fun: I spoke at dropbox!

10 0.28821364 57 hilary mason data-2011-05-21-An Introduction to Machine Learning with Web Data is now available!

11 0.27754521 114 hilary mason data-2013-12-18-Using Twitter’s Lead-Gen Card to Recruit Beta Testers

12 0.24359338 55 hilary mason data-2011-03-27-Gitmarks: a peer-to-peer bookmarking system

13 0.24039601 103 hilary mason data-2013-06-04-Lucene Revolution Keynote: Search is Not a Solved Problem

14 0.23810677 81 hilary mason data-2013-01-03-Interview Questions for Data Scientists

15 0.23244636 94 hilary mason data-2013-03-08-Speaking: Title Slides + Twitter = You Win

16 0.2148173 25 hilary mason data-2009-02-10-JWU Guest Lecture: Introduction to JavaScript and AJAX

17 0.20705451 77 hilary mason data-2012-09-18-Hey Yahoo, You’re Optimizing the Wrong Thing

18 0.2003352 107 hilary mason data-2013-08-31-In Search of the Optimal … Cheeseburger

19 0.18150538 51 hilary mason data-2011-02-11-Interview on Silicon Angle TV

20 0.18005913 73 hilary mason data-2012-07-04-Devs Love Bacon: Everything you need to know about Machine Learning in 30 minutes or less


similar blogs computed by lda model

lda for this blog:

topicId topicWeight

[(2, 0.109), (21, 0.579), (56, 0.078), (63, 0.079)]

similar blogs list:

simIndex simValue blogId blogTitle

1 0.97724783 107 hilary mason data-2013-08-31-In Search of the Optimal … Cheeseburger

Introduction: In Search of the Optimal … Cheeseburger Posted: August 31, 2013 | Author: Hilary Mason | Filed under: Presentations | Tags: cheeseburgers , ignite , talks | 8 Comments » My ignite talk from last year’s data-centric Ignite spectacular is finally up! This was about a fun, personal project, where I was playing with NYC menu data.

same-blog 2 0.9269172 53 hilary mason data-2011-03-11-Conference: PyCon 2011 Keynote!

Introduction: Conference: PyCon 2011 Keynote! Posted: March 11, 2011 | Author: hilary | Filed under: blog , Presentations | Tags: conference , conferences , pycon , python | 1 Comment » I gave the opening keynote this morning at PyCon . The one thing that everyone in the room at PyCon has in common is that we all love to code. I used that as the central theme of the talk, spoke about the constructs that give us joy, the history of some of our favorite patterns (they date as far back as the 60s!) and proposed that we think about the way we’ll compute fifty years into the future. There’s also a bit of fun data hacking, of course. PyCon 2011 Keynote View more presentations from Hilary Mason . Enjoy the slides. The video is up! Please let me know here or on Twitter if you have any questions or comments.

3 0.21483752 93 hilary mason data-2013-03-01-Speaking: Pick a Vague and Specific Title for Your Talk

Introduction: Speaking: Pick a Vague and Specific Title for Your Talk Posted: March 1, 2013 | Author: Hilary Mason | Filed under: speaking | Tags: presentations , speaking , title | Leave a comment » Your title should be both vague and specific . First, vague . You generally have to commit to give a talk months in advance of the actual event. You do not, however, generally have a talk written several months ahead of the actual event. You may also have a particular talk accepted, and then arrive at the conference and realize that what you had planned isn’t ideal for that audience. A vague title offers you a lot of flexibility in altering the content of your talk as conditions change without betraying the expectations of the audience based on the materials published earlier. And then, specific . If your title is too vague (“Stuff and Junk”) people won’t be excited for your talk, and you’ll lack an audience entirely or won’t make it through the CFP process at all. Be s

4 0.20949343 37 hilary mason data-2009-11-25-IgniteNYC: How to Replace Yourself with a Very Small Shell Script

Introduction: IgniteNYC: How to Replace Yourself with a Very Small Shell Script Posted: November 25, 2009 | Author: hilary | Filed under: blog , Presentations | Tags: email , ignitenyc , presentations , scripts | 15 Comments » I recently gave a talk at IgniteNYC on How to Replace Yourself with a Very Small Shell Script . The Ignite events are a fun blend of performance, technology, and speaking skill. Each presenter gives a five minute talk with twenty slides that auto-advance after 15 seconds. The title of my talk is a classic geek reference (you can get the t-shirt ). I’m very interested in developing automated techniques for handling the massive and growing amounts of information that we all have to deal with. I started with e-mail and twitter, both of which are easy to access programmatically (via IMAP and the Twitter API ). In the talk, I went through several of the simple and successful e-mail management scripts that I’ve developed. I decided to

5 0.20723347 105 hilary mason data-2013-07-05-Speaking: Spend at least 1-3 of the time practicing the talk

Introduction: Speaking: Spend at least 1/3 of the time practicing the talk Posted: July 5, 2013 | Author: Hilary Mason | Filed under: speaking | 3 Comments » This week we welcome a guest contribution. Matthew Trentacoste is a recovering academic and a computer scientist at Adobe, where he writes software to make pretty pictures. He’s constantly curious, often about data, and cooks a lot. You can follow his exploits at @mattttrent . In Hilary’s last post, she made the point that your slides != your talk . In a well-crafted talk, your message — in the form of the words you say — needs to dominate while the slides need to play a supporting role. Speak the important parts, and use your slides as a backdrop for what you’re saying. Hilary has provided a valuable strategy in her post, but how should someone approach crafting such a clearly-organized presentation? If you’re just getting started speaking, it can be a real challenge to make a coherent talk and along with slid

6 0.19915515 30 hilary mason data-2009-06-01-My Barcamp Presentation: Have Data? What Now?!

7 0.19855618 34 hilary mason data-2009-10-16-Data: first and last names from the US Census

8 0.19370602 90 hilary mason data-2013-02-18-One Random Tweet, please.

9 0.19126445 60 hilary mason data-2011-08-21-What do you read that changes the way you think?

10 0.18515161 114 hilary mason data-2013-12-18-Using Twitter’s Lead-Gen Card to Recruit Beta Testers

11 0.18458642 94 hilary mason data-2013-03-08-Speaking: Title Slides + Twitter = You Win

12 0.18345337 91 hilary mason data-2013-02-22-Why YOU (an introverted nerd) Should Try Public Speaking

13 0.18326205 24 hilary mason data-2009-01-31-WordPress tip: Move comments from one post to another post

14 0.18231508 80 hilary mason data-2012-12-28-Getting Started with Data Science

15 0.17544968 63 hilary mason data-2011-09-26-Hacking the Food System: The Ultimate Chocolate Chip Cookie

16 0.17379317 83 hilary mason data-2013-01-10-Book Book — Goose!

17 0.17048554 4 hilary mason data-2007-06-11-Teaching Search Techniques with Google Games

18 0.17017464 82 hilary mason data-2013-01-08-Bitly Social Data APIs

19 0.16909745 85 hilary mason data-2013-01-19-Startups: How to Share Data with Academics

20 0.16769168 113 hilary mason data-2013-11-22-Speaking: Two Questions to Ask Before You Give a Talk