We're reflecting on 2023 with insights from 11 data scientists and industry experts. 🤔 Tune into the latest episode of the #DataSciencePodcast to discover the coolest data science revelations of the past year, from the impact of peripheral devices to the complexities of working with large language models: https://spoti.fi/48yPNBS
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Understanding what it means to translate a business question into a predictive question is KEY in adopting AI Ori Sagi Yehonathan Barnea
One of the challenges of traditional data science is deciding precisely how to build a model to match the business's needs. Too often, models end up being irrelevant and disconnected from the problems they were intended to tackle. With Pecan's Predictive GenAI, we've it easy to avoid that problem with our intuitive, easy-to-use Predictive Chat. Watch our very own Ori Sagi explain in a clip from our recent In a Nutshell live event, and read his tips about defining the right predictive question to guide modeling on our blog: https://lnkd.in/ggKiUXJF
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🎓 Day 11 of #MLDailyChallenge: Unravelling Gradient Descent Intuition! 📈 Today, we dove deep into the heart of machine learning, the Gradient Descent Intuition .💡 It's a dance of precision and efficiency, optimizing every step towards smarter solutions. 💃 Let's embrace the journey, mastering the art of data science! 🚀 #MachineLearning #DataScience #pepchallenge
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One of the challenges of traditional data science is deciding precisely how to build a model to match the business's needs. Too often, models end up being irrelevant and disconnected from the problems they were intended to tackle. With Pecan's Predictive GenAI, we've it easy to avoid that problem with our intuitive, easy-to-use Predictive Chat. Watch our very own Ori Sagi explain in a clip from our recent In a Nutshell live event, and read his tips about defining the right predictive question to guide modeling on our blog: https://lnkd.in/ggKiUXJF
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While correlation does not imply causation, many data science practitioners find it hard to understand. I had a tough time too. Lately, I've discovered some impressive resources to learn and deepen my understanding in the realm of causal inference. This video lecture series covers fundamental concepts applied with statistics and machine learning. Thanks to Brady Neal for making it available. https://lnkd.in/gKFPTiy4 #causalInference #inferentialstatistics
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R&D | Continuous Innovation | AI | Semantic Web | Linked Data at Data Archiving and Networked Services (DANS)
Our presentation for the Croissant ML working group on the integration of Croissant standard in Dataverse, covering the present and the future of Machine Learning ready data landscape https://lnkd.in/ehkwuzpf
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Missed one of our insightful webinars? Don't worry! You can catch all our past webinars and more on our YouTube Channel. Subscribe to DSC's YouTube channel to stay updated with the latest trends, insights, and discussions in the world of data science, AI, and analytics! 👉 Subscribe here: https://lnkd.in/g8J6j33Q Why subscribe? 🕵️♂️ Access to exclusive webinars and event replays 🌐 Learn from top data science professionals and industry leaders 📈 Stay ahead with cutting-edge content Hit the subscribe button and never miss out on valuable knowledge and industry updates!
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Early career data scientist and recent graduate. Relentlessly positive and excited to learn and grow.
I know I am connected with a lot of academic folks trying to make the transition to industry, and that starts with a resumé. Building a resumé is a daunting task, but there are straightforward steps to making a good one. Check out this video from Data Science With Dennis for all the tips you'll ever need!
AI & Data Science Chat With A Chief Data Scientist - LIVE AI & Data Science Discussion
https://www.youtube.com/
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Exciting News! Prof. John Wang's latest insights on Encyclopedia of Data Science and Machine Learning. Dive into the world of cutting-edge research and stay ahead in your field. His expertise and contributions are making waves in the academic world. Check out the article to learn more about his impactful work: https://buff.ly/3ufRN2K #MachineLearning #AcademicExcellence #ArtificalIntelligence
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Data generalist // Author of Solve Any Data Analysis Problem // Educator // Co-host of the Half Stack Data Science podcast
How the podcast tables have turned! I spoke to Henry Suryawirawan about skill gaps between data education and industry, and of course my favourite topic: how to solve real data problems (the kind we talk about on Half Stack Data Science). Let me know what you think!
David Asboth is the author of “Solve Any Data Analysis Problem” and co-host of the Half Stack Data Science. In this episode, he shares practical tips for solving real-world data analysis challenges. We also discuss data analysis best practices and the current impact of AI on data analysis. Listen now 👇 🎧Website: https://lnkd.in/dQpDreBz 🎧YouTube: http://rb.gy/6bug3m 🎧Spotify: http://rb.gy/gh8fh4 🎧Apple: http://rb.gy/6mybko
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Come join me at the #Qual360 conference in Berlin this February on the 22nd and 23rd! I'll be chatting about the future fit of qualitative research, where providing context and nuance in an increasingly data-driven environment is key. I'll even dive into how transformational methods used in the Reddit Recommends research can give qual a front-row seat along with our data science and machine learning techniques. See you all there for a balmy February getaway. ❄️ #qualitativeresearch #sociallistening #research #reddit
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