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International Astronomy Meetings - Canadian Astronomy Data Centre. This list of astronomy meetings was originally compiled by Liz Bryson, the now retired librarian of the Canada-France-Hawaii Telescope Corporation, from 1996 to 2011.
The list is currently archived and maintained by the Canadian Astronomy Data Centre (CADC) of NRC Herzberg. Use the Search menu to view meetings by month or year or by keyword. Included with each entry of the Meetings List are links to the meeting web page, contact e-mail addresses, and abstracts provided by NASA's Astrophysics Data System (ADS) if, and when they are available. To add a meeting to the Meetings List or modify information for an existing meeting entry use the Submit or Edit Meeting menu. Fill out the displayed form and submit it. [1603.07342] BEANS - a software package for distributed Big Data analysis.
Visual Cinnamon - Data Visualization and Data Art. Expoartesanías - Corferias. Astronomer H-R diagram. Most people who've done an astronomy course will have heard of the Hertzsprung-Russell diagram.
It was developed to show the relationships between the temperature (or colour) of a star and its luminosity.
ADP Workforce Now. [1501.06586] GalPak3D: A Bayesian parametric tool for extracting morpho-kinematics of galaxies from 3D data. Vistos - La France au Brésil - Consulat Général de France à São Paulo. Writing a LinkedIn Profile. LinkedIn is, for many professionals, the essential professional networking tool of the moment.
There is no question that potential employers and new contacts are likely to look at your LinkedIn profile before they meet you. LinkedIn is also a really good way of keeping up to date with colleagues who you wouldn’t describe as friends exactly, but who you would like to stay in touch with professionally. So what does it take to write a really good LinkedIn profile? It’s surprisingly easy if you follow a few simple guidelines. LinkedIn is a professional networking tool. Camiseta Digital. 10 Ensaladas que demuestran que comer sano es muy sabroso. Ensalada de tomate, mozzarella, garbanzos y pesto twopeasandtheirpod.
Ofertas - Quintal da Leontina. Dicas de Como Perder Barriga em 1 Semana. Graphics - Does anybody know a good source of (free) ornaments, decorations, frames, backgrounds etc.? Fancy Styled Borders in LaTeX. Heavens-Above. What PhDs do wrong (and right!) when applying for Data Science jobs. As a team with an opening for data scientists, we see lots of applications from people with quantitative PhDs.
As someone who did a PhD myself, I’m really excited about what someone with this level of research experience can bring to our team. Getting a PhD in a quantitative hard or social science field requires tenacity, long term planning, a mix of broad technical skills, and clarity of communication about why your work matters to different audiences. Who wouldn’t want someone like that on their team? Nearly half of people working as data scientists today have PhDs, though they make up less than 2% of people in the US over 25, so your academic training will command some attention: “The inventor of LinkedIn’s People You May Know was an experimental physicist. Unfortunately, there’s a gap between the rhetoric pushing PhDs to industry jobs and what is necessary to actually get those jobs. Make Your Case. Creating a great data science resume. I hear a familiar story from a lot of aspiring data scientists: “I have sent out my resume to 25 companies, and I haven’t heard back from any of them!
I have pretty good skills, and I think I have a pretty good resume. I don’t know what’s going on!” Your resume probably sucks. Installing some R packages – Allan Costa. I’m doing Coursera’s Specialization in Data Science and right now I’m in the third course of it, called Getting and Cleaning Data.
In order to answer this week quiz, I needed to install some R packages to load files in different formats. It took me some time to do it, so I’ll document my steps here for anyone that may have trouble doing it. Installing xlsx package. Intro to Machine Learning Course. Java - error: unable to load installed packages just now. Data Analytics and Data Science Skills. Science to Data Science. A Visual Introduction to Machine Learning. Finding better boundaries Let's revisit the 240-ft elevation boundary proposed previously to see how we can improve upon our intuition.
Clearly, this requires a different perspective. By transforming our visualization into a histogram, we can better see how frequently homes appear at each elevation. While the highest home in New York is ~240 ft, the majority of them seem to have far lower elevations. Your first fork. Hired - Marketplace Recruiting Software for Hiring Top Talent. Who are your candidates?
We actively bring on Engineers (new Stanford grads all the way to CTOs), UX/UI Designers, Data Scientists and occasionally Product Managers with experience at venture-funded companies. We also have client-facing professionals, including Account Executives, Account Managers, and Sales Development and Customer Success Professionals. Our focus is on candidates in London, SF, NYC, Boston, LA, Seattle, Austin, Washington DC, Chicago, and candidates willing to relocate to these cities. Machine Learning Mastery. Kaggle: The Home of Data Science. DrivenData. R Statistics - DataJoy - Online Python and R editor. Coursera Inference Version 3. Upload Brian Caffo Loading...
Working... ► Play all Coursera Inference Version 3 Brian Caffo38 videos50,304 viewsLast updated on Feb 18, 2015 Play all Sign in to YouTube Sign in History. El Libro Total - La Biblioteca digital de América. El Pescador x y acceder a otros servicios debe registrarse como lector. EURAXESS Science Slam Brazil - Splash. Insight Data Science Fellows Program. Science to Data Science Virtual. Solve a real-life, big data problem We believe in learning by doing.
The main coursework will be to complete a real life big data problem supplied by our sponsor companies. The project, which will run throughout the five weeks, will be solved in teams of 3-4 and is full time, intensive work. Practical, professional development. Www.scma6.org. Science Gallery. 13 Exercises for Photographers That Can Help Jump-Start Creativity. Like the world’s tidal waters, photographic creativity ebbs and flows for many of us. Sometimes creativity can use a jump-start, an artificial method to get the photographer to start looking at the world in a new way in order to facilitate, restart, refine, or improve your photography. 101 LIGHTROOM PRESETS PACK. With this mega pack of 101 Lightroom® presets, enhancing your images will be a breeze! You’ll: And it couldn’t be easier. All you need to do is apply the effect, adjust as desired – and voilà!
What could normally take days can be achieved in a matter of minutes…. even seconds. How to Shoot the Night Sky (Introduction to Astrophotography) The following post on photographing the night sky is by jgomez65 – one of dPS’s forum members. Several people asked me to post a simple tutorial on how I took some night sky pictures. I am not an astrophotographer in any way, shape or form, nor do I have any expensive equipment. I simply read several tutorials, picked a dark spot on the beach and tried to do my best. Anyway, here is how I did it. 1. You need a camera that has manual exposure mode. Torfs Brauer-Short-R-Intro. RStudio - Download RStudio. Installing R in Ubuntu. Universe The current version of R available when a new version of Ubuntu is released is always available in the universe repository. To install R: sudo apt-get install r-base r-base-dev This will install R, the recommended packages, and files needed to install many additional packages (but not all) from within R using install.packages("foo").
The R packages found in the universe repository are not updated when new versions of R or the recommended packages are released. CRAN has current versions of R and the recommended packages available for all currently supported versions of Ubuntu. Amada by RafaelSdeSouza. Welcome to the AMADA - Analysis of Muldimensional Astronomical DAtasets AMADA allows an iterative exploration and information retrieval of high-dimensional data sets. This is done by performing a hierarchical clustering analysis for different choices of correlation matrices and by doing a principal components analysis in the original data. Additionally, AMADA provides a set of modern visualization data-mining diagnostics. The user can switch between them using the different tabs. Cosmostatisticsinitiative.shinyapps. Learn R with R tutorials and coding challenges. WWF Just.