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Thank you for subscribing to Smash Notes weekly. Every update is a little different. If you see something you particularly like, please let me know. Click to see all the top choices for this week in one place. What is in this update? In no particular order:   Business:  Why would a multi billion dollar business be suing a small coffee shop, and what does it cost to defend yourself from a frivolous lawsuit? Startups:  Working on an idea, are you? What should you validate first? Ryan Hoover from Product Hunt shares his wisdom. It ain't easy. History: What's the big deal with the Second Amendment? Should we all have a gun already? Adam Conover started a new podcast called "Factually!" and on this episode he's invited a guest to talk about the Constitution, gun rights, and other fun history  things. Education: How do you educate your kids if you are a Billionaire? Josh Dahn, the head of Ad Astra, the school founded by Elon Musk, talks about their approach to creative teaching. It's fascinating, and I would almost work for Space X just to have my kids go there, almost. Machine Learning: Microsoft is tired of paying big bucks for data processing and is looking into new ways to do machine learning. They are calling it "Machine Teaching." What is it and why is it so much better?

Coffee Sessions #55 with Salwa Muhammad, Learning and Teaching MLOps Applications.   //Abstract Salwa shared her perspective on how FourthBrain and all learners can keep their education strategy fresh enough for the current zeitgeist. Furthermore, Salwa, Demetrios, and Vishnu talked about principles of effective learning that are important to keep in mind while embarking on any educational journey.   This was a great conversation with a lot of practical tips that we hope you all listen to! // Bio Salwa Nur Muhammad is the Founder/CEO of FourthBrain, an AI/ML education startup backed by Andrew Ng's AI Fund. FourthBrain trains Machine Learning engineers through a hybrid 2-3 month cohort-based programs that combine accountability of weekly instructor-led live sessions with the flexibility of online content. Salwa founded FourthBrain after executive leadership roles at Udacity and Trilogy Education Services (acquired by 2U Inc).    She has over 10 years of experience leveraging technology to develop scalable education programs at higher-ed institutions and ed-tech companies, building new business units, launching international programs, and hiring and training cross-functional teams. // Relevant Links https://www.fourthbrain.ai/ --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/ Connect with Salwa on LinkedIn: https://www.linkedin.com/in/salwanur/ Timestamps: [00:00] Introduction to Salwa Muhammad [01:20] Salwa's journey in tech [05:30] Advice to new ML engineers [10:21] Curriculum development process [17:36] FourthBrain's current status and what's next [21:53] Hardest piece in the course [24:49] Knowing the right job in a role confused world [30:05] Needing to upskill without going insane [35:10] Generalist vs Specialist on T-shaped Analogy [41:15] Counseling learners in terms of long-term progression [43:00] MLOps trajectories recommendation

MLOps community meetup #49! Last Wednesday we talked to Lak Lakshmanan, Data Analytics and AI Solutions, Google Cloud. // Abstract: Design patterns are formalized best practices to solve common problems when designing a software system. As machine learning moves from being a research discipline to a software one, it is useful to catalogue tried-and-proven methods to help engineers tackle frequently occurring problems that crop up during the ML process. In this talk, I will cover five patterns (Workflow Pipelines, Transform, Multimodal Input, Feature Store, Cascade) that are useful in the context of adding flexibility, resilience and reproducibility to ML in production. For data scientists and ML engineers, these patterns provide a way to apply hard-won knowledge from hundreds of ML experts to your own projects. Anyone designing infrastructure for machine learning will have to be able to provide easy ways for the data engineers, data scientists, and ML engineers to implement these, and other, design patterns. // Bio: Lak is the Director for Data Analytics and AI Solutions on Google Cloud. His team builds software solutions for business problems using Google Cloud's data analytics and machine learning products. He founded Google's Advanced Solutions Lab ML Immersion program and is the author of three O'Reilly books and several Coursera courses. Before Google, Lak was a Director of Data Science at Climate Corporation and a Research Scientist at NOAA. ----------- Connect With Us ✌️-------------    Join our Slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Lak on LinkedIn: https://www.linkedin.com/in/valliappalakshmanan/ Timestamps: [00:00] TWIML Con Debate announcement to be hosted by Demetrios on Friday [00:19] Should data scientists know about Kubernetes? Is it just one machine learning tool to rule them all? Or is it going to be the "best-in-class" tool? [00:35] Strong opinion of Lak about "Should data scientists know about Kubernetes?" [05:50] Lak's background into tech [08:07] Which ones you wrote in the book? Is the airport scenario yours? [09:25] Did you write ML Maturity Level from Google? [12:34] How do you know when to bring on perplexity for the sake of making things easier? [16:06] What are some of the best practices that you've seen being used in tooling?   [20:09] How did you come up with writing the book? [20:59] How did we decide that these are the patterns that we need to put in the book? [24:14] Why did I get the "audacity" to think that this is something that is worth doing? [31:29] What would be in your mind some of the hierarchy of design patterns? [38:05] Are there patterns out there that are yet to be discovered? How do you balance the exploitable vs the explorable ml patterns? [42:08] ModelOps vs MLOps [43:08] Do you feel that a DevOps engineer is better suited to make the transition into becoming a Machine Learning engineer? [46:07] Fundamental Machine Design Patterns vs Software Development Design Patterns [49:23] When you're working with the companies at Google, did you give them a toolchain and a better infrastructure or was there more to it? Did they have to rethink their corporate culture because DevOps is often mistaken as just a pure toolchain?

In this episode we continue to explore the different assessment types by taking a look at Assessments for Learning (aka Formative Assessments).  We start by sharing a few analogies (Cooking/Dress Rehearsal/Journey) to frame and define assessments for learning, then we discuss some classroom examples that teachers can use before wrapping up with a discussion which brings home the point that both Assessments of and Assessments for Learning are needed for teachers and students in the instructional cycle. References: ASCD - Formative Assessment: Why, What, and Whether Educational Sciences - The Effects of Formative Assessments Theme song provided by Cary High School student Logan Foster Hosts: Mellisa Smith, Serena Halstead, and Spencer Ziegler Data, Research, and Accountability department for the Wake County Public School System . --- Send in a voice message: https://anchor.fm/datalit/message

The approach to Learning and Development has remained unchanged and the only shift has been in the delivery medium. Here is an exploration of what it could be.

This is the first episode of a podcast series on Machine Learning and Data privacy.  Machine Learning is the key to the new revolution in many industries. Nevertheless, ML does not exist without data and a lot of it, which in many cases results in the use of sensitive information. With new privacy regulations, access to data is today harder and much more difficult but, does that mean that ML and Data Science has its days counted? Will the Machines beat privacy?   Don't forget to subscribe to the mlops.community slack ( https://go.mlops.community/slack ) and to give a star to the Synthetic data open-source repo ( https://github.com/ydataai/ydata-synt... ) Useful links:   Medium post with the podcast transcription - https://medium.com/@fabiana_clemente/... In case you're curious about GDPR fines - enforcementtracker.com   The Netflix Prize - https://www.nytimes.com/2010/03/13/technology/13netflix.html Tensorflow privacy - https://github.com/tensorflow/privacy

Coffee Sessions #28 with Charlie You of Workday, Lessons learned from hosting the Machine Learning Engineered podcast //Bio Charlie You is a Machine Learning Engineer at Workday and the host of ML Engineered, a long-form interview podcast aiming to help listeners bring AI out of the lab and into products that people love. He holds a B.S. in Computer Science from Rensselaer Polytechnic Institute and previously worked for AWS AI. Charlie is currently working as a Machine Learning Engineer at Workday. He hosts the ML Engineered podcast, learning from the best practitioners in the world.   Check Charlie's podcast and website here: mlengineered.com https://cyou.ai/ --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/ Connect with Charlie on LinkedIn: https://linkedin.com/in/charlieyou/ Timestamps: [00:00] Introduction to Charlie You [01:50] Charlie's background on Machine Learning and inspiration to create a podcast [06:20] What's your experience been so far as the machine learning engineer and trying to put models into production and trying to get things out that has business value? [07:08] "I started the podcast because as I started working, I had the tingling that machine learning engineering is harder than most people thought, and like way harder than I personally thought." [08:20] What's an example of that where you target someone in your podcast, you keep that learning and you want an extra meeting the next day and say "Hey, actually I'm starting one of the world's experts on this topics and this is what they said"?    [10:06] In a world of tons of traditional software engineering assets and the process you put in place, how have they adopted what they're doing to the machine learning realm?    [19:00] About your podcast, what are some 2-3 most consistent trends that you've been seeing? [21:08] Instead of splintering so much as machine learning monitoring infrastructure specialist, are you going to departmentalize it in the future? [27:22] Is there such a thing as an MLOps engineer right now? [28:50] "We haven't seen a very vocal, very opinionated project manager in machine learning yet." - Todd Underwood [30:18] "Similarly with tooling, we haven't seen the emergence of the tools that encode those best practices." Charlie [31:42] "The day that you don't have to be a subject matter expert in machine learning to feel confident and deploy machine learning products, is the day that you will see the real product leadership in machine learning." Vishnu [34:12] I'd love to hear your take on some more trends that you've been seeing (Security and Ethics) [34:41] "Data Privacy and Security is always at the top of any consideration for infrastructure." Charlie [35:44] That's driven by legal requirements? How do you solve this problem? [37:27] How do we make sure that if that blows up, you're not left with nothing?   [42:28] In your conversations, have you seen people who goes with cloud provider? [43:25] Enterprises have much different incentives than startups do. [45:48] What are some used cases where companies are needing to service their entire needs? [45:48] What are some used cases where companies are needing to service their entire needs? [49:18] What are some takeaways that you had in terms of how you think about your career, what experiences you want to build as this MLOps based engineering is moving so fast?   [56:08] "Your edge is never in the algorithm"

The latest episode of 2 Minute Drill, a Minicast From Diversified Game, features Tiffany Simmons of World Views.  World Views Travel Group is a distinct group that's comprised of people who love to travel. On our traveling adventures, we like to experience the people, the culture, the food and local traditions. We are \"Travel Junkies\" at heart, adventure seekers. Instagram: http://instagram.com/worldviewstraveljunkies Facebook: https://www.facebook.com/WorldViewstravelgroup Website: https://www.worldviewswv.com If you are a new listener to 2 Minute Drill, a Minicast from Diversified Game, we would love to hear from you.  Please visit our Contact Page and let us know how we can help you today! To Stay Updated Join Our Email List: http://subscribe.diversifiedgame.com Submit to Be Featured:   http://2minutedrill.diversifiedgame.com Follow the Diversified Game Podcast Instagram: http://instagram.diversifiedgame.com Twitter: http://twitter.diversifiedgame.com Facebook: http://facebook.diversifiedgame.com YouTube: http://youtube.diversifiedgame.com SoundCloud: http://soundcloud.diversifiedgame.com Website: http://diversifiedgame.com Follow the Diversified Game Host(s) Kellen Coleman - Instagram: http://instagram.com/kellenkash , Twitter: http://twitter.com/kellenkash   Tyson Moultrie - Instagram: http://instagram.com/typhoenixlive , Twitter: http://twitter.com/typhoenixlive A.L. Roberts - Instagram: http://instagram.com/alrtistry , Twitter: http://twitter.com/alrtistry Join the Conversation Our favorite part of recording a podcast each week is participating in the great conversations that happen so, join in the convo on social media, and in our comments section.  Leave a review if you like the direction the show is going! If, not visit us and give some feedback on how to improve, Thanks! Join our Community  You can always follow us on social media, but for the growing log of super exclusive stuff visit our Patreon Community: http://patreon.diversifiedgame.com   --- Support this podcast: https://podcasters.spotify.com/pod/show/2-Minute-Drill/support

**AI and ethical dilemmas** Artificial Intelligence is seen by many as a vehicle for great transformation, but for others, it still remains a mystery, and many questions remain unanswered: will AI systems rule us one day? Can we trust AI to rule our criminal systems? Maybe create political campaigns and dominate political advertisements? Or maybe something less harmful, do our laundry? Some of these questions may sound absurd, but they are for sure making people shift from thinking purely about functional AI capabilities but also to look further to the ethics behind creating such powerful solutions.   For this episode we count with Charles Radclyffe as a guest, the data philosopher, to cover some of these dilemmas. You can reach out to Charles through LinkedIn or at ethicsgrade.io   Useful links:   - MLOps.Community slack - TEDx talk - Surviving the Robot Revolution - Digital Ethics whitepaper

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With the advent of the Internet it is now possible to collect hundreds of millions of images. These images come with varying degrees of label information. “Clean labels” can be manually obtained on a small fraction, “noisy labels” may be extracted automatically from surrounding text, while for most images there are no labels at all. Semisupervised learning is a principled framework for combining these different label sources. However, it scales polynomially with the number of images, making it impractical for use on gigantic collections with hundreds of millions of images and thousands of classes. In this paper we show how to utilize recent results in machine learning to obtain highly efficient approximations for semi-supervised learning. Specifically, we use the convergence of the eigenvectors of the normalized graph Laplacian to eigenfunctions of weighted Laplace-Beltrami operators. We combine this with a label sharing framework obtained from Wordnet to propagate label information to classes lacking manual annotations. Our algorithm enables us to apply semi-supervised learning to a database of 80 million images with 74 thousand classes.

With the advent of the Internet it is now possible to collect hundreds of millions of images. These images come with varying degrees of label information. “Clean labels” can be manually obtained on a small fraction, “noisy labels” may be extracted automatically from surrounding text, while for most images there are no labels at all. Semisupervised learning is a principled framework for combining these different label sources. However, it scales polynomially with the number of images, making it impractical for use on gigantic collections with hundreds of millions of images and thousands of classes. In this paper we show how to utilize recent results in machine learning to obtain highly efficient approximations for semi-supervised learning. Specifically, we use the convergence of the eigenvectors of the normalized graph Laplacian to eigenfunctions of weighted Laplace-Beltrami operators. We combine this with a label sharing framework obtained from Wordnet to propagate label information to classes lacking manual annotations. Our algorithm enables us to apply semi-supervised learning to a database of 80 million images with 74 thousand classes.

\"You must prepare a place before you can plant the seed\". Getting yourself and your mule into a learning frame of mind is crucial to success. I've found that when I am mentally comfortable and my mule is the same, we make a lot more progress. I hope you enjoy this episode! www.tsmules.com

\"You must prepare a place before you can plant the seed\". Getting yourself and your mule into a learning frame of mind is crucial to success. I've found that when I am mentally comfortable and my mule is the same, we make a lot more progress. I hope you enjoy this episode! www.tsmules.com

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Will bad coding practices in the company hinder my learning?

Video content can be found here: https://www.youtube.com/channel/UC0BAd8tPlDqFvDYBemHcQPQ/

Preparing for the start of the year, 

Subscribe to the transcripts at https://www.allearsenglish.com/subscribe Are you under the illusion of fluency? In this episode I interview Jeff from Interlink International Institutes and he shows us 3 scientific principles that you can apply when you learn English to be sure you reach the level of fluency and confidence that you're looking for

The bumpy road that the Communist Party took in Shanghai as it developed its capacity to deploy organized violence as a political tactic.Further reading:Steve Smith, A Road Is Made: Communism in Shanghai, 1920-1927Some names from this episode:Wang Shouhua, Leading Communist labor organizer in ShanghaiYu Xiaqing, Leader of a nationalist faction of Shanghai's merchant classNiu Yongjian, Veteran Nationalist operative who came to Shanghai in 1926Sun Chuanfang, Leader of warlord coalition in China's southeastTao Jingxuan, Communist union organizer executed after First Armed UprisingChen Duxiu, General Secretary of the Communist PartySupport the show (https://www.paypal.com/donate?hosted_button_id=DACDMMMEASJVJ)

In today's episode, we discuss what it takes to create a learning environment that can get your gears turning immediately.Today's episode is brought to you by Linode. Linode Provides superfast SSD based Linux servers in the cloud starting at $5 a month. Linode is offering Developer Tea listeners $20 worth of credit if you use the code DEVELOPERTEA2017 at checkout. Head over to spec.fm/linode to learn more about what Linode has to offer to Developer Tea listeners .

Get out of your mental rut by blocking out things and negative people that do not matter! This is the final part of this powerful business coach led series on the Thrivetime Show.

Teresa HisChase joins the show to discuss the Northern Arapaho language, history, and shares both stories and wisdom. She has worked on creating the first ever Arapaho language app. The show is recorded in the Porter's 10Cast Studio. It's made possible by the Wyoming Department of Transportation and by the Institute of Tribal Learning at Central Wyoming College. Follow Indian Relay on Facebook or Instagram!

Teresa HisChase joins the show to discuss the Northern Arapaho language, history, and shares both stories and wisdom. She has worked on creating the first ever Arapaho language app. The show is recorded in the Porter's 10Cast Studio. It's made possible by the Wyoming Department of Transportation and by the Institute of Tribal Learning at Central Wyoming College. Follow Indian Relay on Facebook or Instagram!

Teresa HisChase joins the show to discuss the Northern Arapaho language, history, and shares both stories and wisdom. She has worked on creating the first ever Arapaho language app. The show is recorded in the Porter's 10Cast Studio. It's made possible by the Wyoming Department of Transportation and by the Institute of Tribal Learning at Central Wyoming College. Follow Indian Relay on Facebook or Instagram!

Teresa HisChase joins the show to discuss the Northern Arapaho language, history, and shares both stories and wisdom. She has worked on creating the first ever Arapaho language app. The show is recorded in the Porter's 10Cast Studio. It's made possible by the Wyoming Department of Transportation and by the Institute of Tribal Learning at Central Wyoming College. Follow Indian Relay on Facebook or Instagram!

Teresa HisChase joins the show to discuss the Northern Arapaho language, history, and shares both stories and wisdom. She has worked on creating the first ever Arapaho language app. The show is recorded in the Porter's 10Cast Studio. It's made possible by the Wyoming Department of Transportation and by the Institute of Tribal Learning at Central Wyoming College. Follow Indian Relay on Facebook or Instagram!

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UPSKILLING : Create a Learning Organization - Competency mapping and assessment--- Support this podcast: https://anchor.fm/abhisek-gupta/support

UPSKILLING : Create a Learning Organization - Competency mapping and assessment--- Support this podcast: https://anchor.fm/abhisek-gupta/support

Learning Lessons From North Korean House Churches And Persecution by Edgar Reich

Dear Diary,Galau juga ya... anak saya sekolah di TK. Dengan ada wabah korona sekarang anak saya sekolah online, Beda banget sama anak yang lebih gede, yang udah SD. Anak saya gak mau diem, hahaha... namanya anak kecil ya.Lalu ada lagi berita akan ada rencana anak-anak kembali ke sekolah dengan ketentuan New Normal. Eh.. galau saya makin-makin deh.Kali ini saya mau dengerin Mom's Diary Podcast, Karena seru bahas kegalauan ini, gimana bantu anak TK sekolah online dan bagaimana kalau harus sekolah di New Normal Era nanti.

In this episode udeme talks about how to handle situations life throughs at you and why self imorovement at you 9-5 is important. Join the conversation on email [email protected] and catch us on Instagram @allthetweseepodcast . Love and Light!!--- Send in a voice message: https://anchor.fm/udemeasian/message

Discussing Google+ and more...

Objective: To map the evidence concerning the use of machine learning (ML) to predict treatment burden and outcomes in patients with nAMD, DMO, and RVO-associated macular oedema in order to understand the current state of the art and the gaps. Introduction: Neovascular age-related macular degeneration (nAMD), diabetic macular oedema (DMO), and retinal vein occlusion (RVO) associated macular oedema are some of the leading causes of visual loss globally.1 Intravitreal anti-vascular endothelial growth factor (VEGF) injections are currently used to treat such diseases.1 The treatment course and outcomes for each patient is variable and thus individualised treatment techniques are needed.2 Two of the most pressing issues are estimating treatment burden (e.g., patients who need fewer vs. more intravitreal injections) and visual prognosis (e.g., good vs. poor responders) in individual patients.2 This research aims to assess the potential of ML to predict treatment burden and outcomes to personalise anti-VEGF treatment in patients with nAMD, DMO, and RVO. We seek to understand the types of ML approaches that have been explored, their maturity, reported outcomes, and real-world applicability. Eligibility criteria: Studies will be included if they focus on ML algorithms that predict anti-VEGF treatment burden and/or outcomes in patients with nAMD, DMO, and RVO-associated macular oedema. The included studies will consist of full-length original research journal articles written or translated into English. We will exclude other types of literature (i.e., not full-length journal articles, not a report of original research and not centred on ML algorithms that predict anti-VEGF treatment burden and/or outcomes in patients with nAMD, DMO, and RVO-associated macular oedema). Publication dates of included studies will be from January 2000 onwards. Methods: Five academic databases will be searched (Ovid Medline, Embase, Web of Science Core Collection, IEEE, and ACM Digital Library). Search strings for each database were formulated in conjunction with a Massachusetts Eye and Ear, Harvard Medical School librarian. Studies will be uploaded to Covidence (literature management software), and duplicates will be removed. Studies will be screened by two independent screeners (SG & AYO). Disagreements will be resolved with a discussion with a third author (DM). SG will conduct a descriptive analysis of the data. We will use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) for reporting our study, and we will publish our protocol on the Open Science Framework (OSF).3 Results: We will report the number and type of included evidence, as well as any pertinent study characteristics. Main topics of interest and significant outcomes will also be presented. Inferences will be presented in an appropriate diagrammatic or tabular format. Conclusions: Based on the key concepts and topics extrapolated from the selected studies, the scoping review will aim to explore the breadth and depth of the current literature and address any knowledge gaps that can hold the potential to inform future research and future algorithm development. Keywords: Intravitreal injections, ophthalmology, artificial intelligence, systematic scoping review

Objective: To map the evidence concerning the use of machine learning (ML) to predict treatment burden and outcomes in patients with nAMD, DMO, and RVO-associated macular oedema in order to understand the current state of the art and the gaps. Introduction: Neovascular age-related macular degeneration (nAMD), diabetic macular oedema (DMO), and retinal vein occlusion (RVO) associated macular oedema are some of the leading causes of visual loss globally.1 Intravitreal anti-vascular endothelial growth factor (VEGF) injections are currently used to treat such diseases.1 The treatment course and outcomes for each patient is variable and thus individualised treatment techniques are needed.2 Two of the most pressing issues are estimating treatment burden (e.g., patients who need fewer vs. more intravitreal injections) and visual prognosis (e.g., good vs. poor responders) in individual patients.2 This research aims to assess the potential of ML to predict treatment burden and outcomes to personalise anti-VEGF treatment in patients with nAMD, DMO, and RVO. We seek to understand the types of ML approaches that have been explored, their maturity, reported outcomes, and real-world applicability. Eligibility criteria: Studies will be included if they focus on ML algorithms that predict anti-VEGF treatment burden and/or outcomes in patients with nAMD, DMO, and RVO-associated macular oedema. The included studies will consist of full-length original research journal articles written or translated into English. We will exclude other types of literature (i.e., not full-length journal articles, not a report of original research and not centred on ML algorithms that predict anti-VEGF treatment burden and/or outcomes in patients with nAMD, DMO, and RVO-associated macular oedema). Publication dates of included studies will be from January 2000 onwards. Methods: Five academic databases will be searched (Ovid Medline, Embase, Web of Science Core Collection, IEEE, and ACM Digital Library). Search strings for each database were formulated in conjunction with a Massachusetts Eye and Ear, Harvard Medical School librarian. Studies will be uploaded to Covidence (literature management software), and duplicates will be removed. Studies will be screened by two independent screeners (SG & AYO). Disagreements will be resolved with a discussion with a third author (DM). SG will conduct a descriptive analysis of the data. We will use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) for reporting our study, and we will publish our protocol on the Open Science Framework (OSF).3 Results: We will report the number and type of included evidence, as well as any pertinent study characteristics. Main topics of interest and significant outcomes will also be presented. Inferences will be presented in an appropriate diagrammatic or tabular format. Conclusions: Based on the key concepts and topics extrapolated from the selected studies, the scoping review will aim to explore the breadth and depth of the current literature and address any knowledge gaps that can hold the potential to inform future research and future algorithm development. Keywords: Intravitreal injections, ophthalmology, artificial intelligence, systematic scoping review

In this episode of Jack of all knowledge, I'm joined by my dear friend and senior Nirmal Bhansali. Nirmal is a 5th year law student at NLUJ, and will be graduating from college this summer. I talk to him about a range of issues, from his experience of hosting two different podcasts, to curiosity and how learning happens inside and outside college. We go off on a bunch of different interesting tangents which makes the conversation richer. Nirmal is on twitter as @NirmalSBhansali.1. Curiousect: https://open.spotify.com/show/3xy0CTHMOHTvuYy2sKNvGA?si=tB-K8hPCQNKPVzC5gpknSg&utm_source=copy-link2. Legal Synthesis (with Sandesh Atyam): https://open.spotify.com/show/22uItKBeS0gcABpxgTrCiQ?si=GR6crqvqR2-o1MZ_2jvSLw&utm_source=copy-link3. 99% Invisible: https://open.spotify.com/show/2VRS1IJCTn2Nlkg33ZVfkM?si=a2vTqf40T42n_sH-67Pi7Q&utm_source=copy-link4. This American Life: https://open.spotify.com/show/41zWZdWCpVQrKj7ykQnXRc?si=vxLJpGRaRyu49bKyTmUG9g&utm_source=copy-link5. More perfect: https://open.spotify.com/show/6iVxbLoqDofkNpXYO4mt2W?si=45m9LFftShOhCxW5V5-aQQ&utm_source=copy-link6. Hello Internet: https://open.spotify.com/show/6qJxqNeEbtFpRVkUchWTRr?si=ta_-LmSDT8WoF85ds_lo2Q&utm_source=copy-link7. The undismal paradox: https://open.spotify.com/show/0E5PReAJtDkKFBhbMKzo4n?si=lOuv0VCSQvSy1rZmFIuQDg&utm_source=copy-link8. Ways of hearing: https://open.spotify.com/episode/5sovOkTvSVAi1VDgKKi74d?si=9rRsh4d8Sh61M6iJu89GcQ&utm_source=copy-link9. Roman Mars's Ted Talk: https://youtu.be/pnv5iKB2hl410. Paul Graham's essay on Curiosity: http://www.paulgraham.com/think.html11. Nirmal's episode titled 'A longing to read': https://open.spotify.com/episode/7BhjVdVNIYLkhGZl7SkI0B?si=Vq6OShcUTNOKlqWFexJ9jw&utm_source=copy-link 12. Max Joseph's video about Bookstore and reading: https://youtu.be/lIW5jBrrsS013. Ashish Kulkarni's (v cool) blog: https://econforeverybody.com/My essays on some related topics:1. The knowledge tradeoff: https://impatientlycurious.blogspot.com/2021/03/the-knowledge-trade-off.html2. Bring back long-form: https://impatientlycurious.blogspot.com/2021/03/bring-back-long-form.html3. Procrastination kills knowledge: https://impatientlycurious.blogspot.com/2021/03/procrastination-kills-knowledge.html4. Inadequacy of knowledge: https://impatientlycurious.blogspot.com/2021/03/inadequacy-of-knowledge.html5. Advice to my 18 y/o self: https://impatientlycurious.blogspot.com/2021/04/advice-to-my-18-year-old-self.html

On this episode of The Grapevine, Kulja and Dylan get on the line with Julie Sonnemann, Acting School Education Program Director at the Grattan Institute to discuss Victoria's $250 million plan to help students who fell behind catch up on their education, and her piece in The Conversation arguing what is necessary for the plan's success. And, how does Australia prosecute war crimes? Rawan Arraf, Principal Lawyer and Director of the Australian Centre for International Justice discusses the instalment of the Office of the Special Investigator within the Department of Home affairs to investigate alleged war crimes perpetrated by Australian special forces in Afghanistan, and his call for a "dedicated and permanent program" to investigate and prosecute Australian war criminals. Then, best-selling author, polymath, and champion of culture and innovation, Barry Jones chats about his new book 'What is to be done: Political engagement and saving our planet'. Following up on his influential book 'When Sleepers, Wake!', Jones explores the changes to work, class, and climate in a post-truth digital era where conversation is dominated by marketing and the manipulation of 'facts' by political figures.

xi, 322 pages : 25 cm

xi, 322 pages : 25 cm

On this week's podcast, Paul Whitehouse and Shaun Ryder stop by; the team learn Mandarin (and Geordie). Dom receives some news regarding Dannii from Babestation. Also, James tries to cover up his Henna tattoo. There's more...-?Pubcast Confession-?The Most Subdued Caller-?Pointless Celebrities-?Classic FM Live Enjoy The Chris Moyles Show on Radio XWeekdays 6:30-10am RadioX.co.uk

Join me on the podcast this week to discover how unhealthy coping mechanisms and reactions might be showing up in your life and how they are affecting your relationships and your experience of the world as a whole. I'm sharing how you can address these problems, where they come from, and what options are available for you to start changing them.Get full show notes and more information here: https://nicolesymcox.com/42

Join me on the podcast this week to discover how unhealthy coping mechanisms and reactions might be showing up in your life and how they are affecting your relationships and your experience of the world as a whole. I'm sharing how you can address these problems, where they come from, and what options are available for you to start changing them.Get full show notes and more information here: https://nicolesymcox.com/42

This this episode "Learning How To Visualize - Part 4" we are going to visualize how you want to perform in an upcoming competition.These are the questions I want you to consider when you are visualizing your competition.When you get out of the car how are you feeling?What are you wearing?What do you need to do to get ready for the warm up prior to your competition?Where do you go to warm up?Your name is called, the whistle has blown... what do you do to walk up to prepare for the start of your game?The Game Begins - how do you begin?Take yourself through the whole sports performance - from the beginning to the end.You have completed your game.Have an absolutely awesome day and remember, Dream Big, Believe In You & Go After Your Dreams.To your abundance,Tiffany MikaP.S. Leave a comment and share with me what you liked best about what you heard today... thank you.Connect With Tiff Here:Instagram: https://www.instagram.com/tiffanymikacox/Facebook: http://facebook.com/tiffanymikatakesactionTwitter: https://twitter.com/tiffanymikaSnapChat: tiffanymika01Website: http://tiffany-mika.comEmail:[email protected]

January 19, 2021, is the release of Steven Kotler's new book, The Art of Impossible.It's $27.99 everywhere books are sold BUT you can only get the book and a battle-tested set of Free Peak Performance Tools and Trainings at ?? https://www.theartofimpossible.com/ Today, I am interviewing our very own Steven Kotler on learning. It is an intimate fireside chat where Steven talks about the right mindset for learning as well as truth filters.The first thing we cover is that the foundation for learning is having a growth mindset. The growth mindset is based on the belief that your basic qualities are things you can cultivate through your efforts. Although people may differ in every which way - in their initial talents and aptitudes, interests, or temperaments - everyone can change and grow through application and experience.Having a \"fixed mindset\" on the other hand alters our underlying neurobiology, making the acquisition of new information exceptionally difficult. So before we can begin learning, we need to believe that learning is possible.Secondly, you will learn what truth filters are and how you can apply them.What really matters is that you create a rigorous truth filter when you learn. You can't learn and grow on bad information.Plus, there are performance benefits to consider. Being able to trust the information you're working with lowers anxiety, doubt, and cognitive load-which are three things that loosen our focus, hamper our ability to get into flow, and block learning itself. It is safe to say: This is a truly exciting episode!---If you order Steven's new book, The Art of Impossible, right now, you'll get $1.500 USD of free bonuses immediately dropped into your inbox. They include secret chapters he has never released, masterclasses on key skills to help you jack up motivation, heighten creativity, and accelerate learning. You'll also get an entirely free training to help you fight distraction and spend more time in flow. So click the link here, snag yourself a copy of The Art of Impossible, and let's get after it. ?? https://www.theartofimpossible.com/

Robby speaks with Trisha Gee, Developer Advocate at JetBrains. They discuss Trisha's role as a Developer Advocate, how open source library maintainers are underappreciated, and how developers can overcome their fear of writing, speaking, and contributing back to the community.

Should devs focus on learning languages or techniques?

Ashley Beaudin is an inspirational speaker, hug-dealer and the visionary of The Imperfect Boss; a movement that is making imperfect normal and inspiring tens of thousands of creative women to grow their confidence. Ashley is passionate about seeing people show up fully as themselves and lead through their gifts, message, and presence.Things we talk about in today's episode:TRIGGER WARNING: Ashley has a history of abuse and we discuss some of her journey with sexual trauma so if that's a triggering thing for you, you may want to skip this week's episode. How entrepreneurship and creating the Imperfect Boss launched her into feeling seen, worthy and loved.?Her journey with online sex addiction as a virgin Where we so often derive our self worth from and how it's so MF backwardsHow to embrace our imperfections Also, we get weird AF as per the usual and embrace our mutual Canadian-ness. Giddy up.