Data Science Weekly - Data Science Weekly - Issue 462

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Issue #462

September 29 2022

Editor's Picks

 

  • Why I teach my students about scientific failure
    With class about to start, I print 14 Western blot images for my students to discuss. The 3-hour lab is supposed to be the culmination of a weeks long research project in my undergraduate biology course, the day my students determine whether their experimental results support their carefully crafted hypotheses. But the images are all the same—and all full of nothing but background bands. My students are about to have a hard lesson in scientific failure and how to be resilient in the face of it...
  • Uncertainty in Deep Learning — Brief Introduction
    In this post, I will try to give an intuition about uncertainty in Deep Learning models instead of explaining these uncertainties in depth. They will be explained in the next parts using TensorFlow Probability...
  • NLP gigs [Twitter Thread]
    Reflecting on NLP gigs, thought I'd summarize a few things an NLP consultant can be expected to know about. 🧵...
 
 

A Message from this week's Sponsor:

 



Observable Insight - October 26 & 27

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  • Dive into what it looks like to collaborate with diverse groups around data
  • Hear from industry leaders who use Observable for data analysis and create data visualizations
  • Learn how to use Observable to promote a shared understanding of data across your organization
  • See examples of how the community is using Observable in journalism, education, and app development
Please join us to see what your data can show - the event is free to attend, so register today.

 

 

Data Science Articles & Videos

 
  • Introducing Make-A-Video: An AI system that generates videos from text
    Today, we’re announcing "Make-A-Video", a new AI system that lets people turn text prompts into brief, high-quality video clips. Make-A-Video builds on Meta AI’s recent progress in generative technology research and has the potential to open new opportunities for creators and artists. The system learns what the world looks like from paired text-image data and how the world moves from video footage with no associated text. As part of our continued commitment to open science, we’re sharing details in a research paper and plan to release a demo experience...
  • Writing Functions in R
    The beauty of R is its versatility and of course the community 💜 you can use R for literally anything (I use blogdown to set up and maintain my website, xaringan to create slide decks, Shiny to build web applications, ….). All these great tools build upon one “little” (or not so little) thing: functions!...
  • DALL·E Now Available Without Waitlist
    New users can start creating straight away. Lessons learned from deployment and improvements to our safety systems make wider availability possible...
  • embetter
    Embetter implements scikit-learn compatible embeddings for computer vision and text. It should make it very easy to quickly build proof of concepts using scikit-learn pipelines and, in particular, should help with bulk labelling. It's a also meant to play nice with bulk and scikit-partial...
  • Machine Learning Integrity
    Yaron Singer on building tools to guard against and reduce model failures...Yaron Singer is the CEO of Robust Intelligence1, a company building tools to help manage and mitigate risks associated with machine learning models and applications. They are specifically creating solutions that integrate seamlessly into the ML lifecycle to guard against and reduce model failures...
  • Supporting the next generation of AI leaders
    We’re partnering with six education charities and social enterprises in the United Kingdom (UK) to co-create a bespoke education programme to help tackle the gaps in STEM education and boost existing programmes through funding, volunteering, and the development of new AI resources...
  • Ways to schedule Jupyter Notebook
    In this post, I will summarize five different approaches for Jupyter Notebook scheduling. I want to cover the following features for each method: 1) where the notebook is executed, locally or in the cloud, 2) is User Interface for schedule management available? 3) option to export notebook to HTML or PDF files, 4) automatically send notebook as an attachment by email, 5) share a link to the executed notebook, 6) restrict access to the notebook for selected (authenticated) users, 7) history of previous executions available in User Interface, 8) parametrized executions with an option to override, 9) hide code in the executed notebook, 10) possibility to execute the notebook as slides...
  • Data Visualisation with Markdown, Flexdashboard and Shiny
    In most data projects it is useful and necessary to visualize your data and your results. Different tools exist for this in the R-universe and it depends on your purpose what is most suitable for you...In the following I will present some data visualization packages and tools that can help you to get the best visualization out of your data...
 
 

Tool*

 



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*Sponsored post. If you want to be featured here, or as our main sponsor, contact us!

 
 

Jobs

 
  • Data Scientist - Success Academy Charter Schools, Inc - NYC

    This new Data Scientist role will be a key contributor to our mission of driving innovation across the organization. Reporting to the Leader of Enterprise Analytics, this role will be responsible for working with stakeholders in various functions to understand areas of opportunity, developing analytical solutions ranging from dashboards to sophisticated mathematical models, and helping functional teams adopt those solutions. This role will be part of a highly collaborative team of professionals with a wide range of skills including data science, data engineering, business analysis, and project management....
     

        Want to post a job here? Email us for details --> team@datascienceweekly.org

 

 

Training & Resources

 
  • Decision Trees in Python: Predicting Diabetes
    In this post, we’ll be learning about decision trees, how they work and what the benefits are for using them. We’ll also use this algorithm in a real-world data to predict diabetes...
  • Serverless Machine Learning
    This course is intended for new and seasoned practitioners of Machine Learning and Data Science with some level of experience programming in Python and working in notebooks environment...In this course, you will build a prediction service, not just train a model...
  • Feature Store Summit 2022
    A Free Virtual Conference for Feature Engineering: Join us this year for more talks on latest technologies, best practices, and use cases for putting machine learning models into production environments....
 
 

What you’re up to – notes from DSW readers

 
  • Fill out the form below to appear here :) ...
 

* To share your projects and updates, share the details here.

** Want to chat with one of the above people? Hit reply and let us know :)

 

Last Week's Newsletter's 3 Most Clicked Links

 

* Based on unique clicks.

** Find last week's newsletter here.



 

Cutting Room Floor

 
  • All clear :)



P.S., Enjoy the newsletter? Please forward it to your friends and colleagues - we'd love to have them onboard :) All the best, Hannah & Sebastian
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