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This week, Jon Krohn dives into the world of object detection and the cutting-edge YOLO-NAS model architecture with Harpreet Sahota, a data science expert and deep learning developer at Deci AI. Tune in for an eye-opening episode on machine vision and the future of AI! 2
/r/superdatascience, 2023-07-04, 12:21:08
What could pink elephants have to do with transformers? Data scientist David Foster explains all this and more in his terminology-rich interview with Jon Krohn. 1
/r/superdatascience, 2023-06-13, 11:57:43
Unlock the power of XGBoost by learning how to fine-tune its hyperparameters and discover its optimal modeling situations. This and more, when best-selling author and leading Python consultant Matt Harrison teams up with Jon Krohn for yet another jam-packed technical episode! 1
/r/superdatascience, 2023-05-23, 11:42:57
This Ph.D. Holder Switched To A Full-Time Data Science Job 1
/r/superdatascience, 2023-05-17, 08:58:56
This week’s episode is critical listening for AI investors and generative AI creators. Learn about the emerging generative AI stack, the critical elements of MLOps to ensure a scalable model, and the tools developers can use for a saleable product. 1
/r/superdatascience, 2023-05-16, 11:19:13
What’s the secret to successful marketing? Analytics expert Avinash Kaushik joins Jon Krohn to reveal the key to commercial success in marketing analytics. Discover the transformative power of AI in marketing, the value of hands-on data tools, and his 'four clusters of intent' framework. 1
/r/superdatascience, 2023-05-09, 11:02:18
Pandas will become your best friend after you’ve listened to this week’s episode with Bloomberg engineer and author Stefanie Molin, who speaks to Jon Krohn about this significant Python library. Tune in here! 1
/r/superdatascience, 2023-05-02, 12:08:31
Attention hands-on Python practitioners! Taipy CEO and co-founder, Vincent Gosselin, joins Jon Krohn to share how you can accelerate your productivity in Python and build scalable, reusable, and maintainable data pipelines 1
/r/superdatascience, 2023-04-25, 11:54:07
🚀 Skyrocket your data science career with the hottest skill of 2023 - Cloud Computing! 🔥 Hadelin and Kirill join Jon Krohn, to dive deep into how to use Cloud for Data Science & Machine Learning, and why a cloud computing accreditation could be your ultimate career game-changer! 1
/r/superdatascience, 2023-04-18, 11:28:54
Co-Founder and Chief Product Officer at Pathway, Adrian Kosowski joins Jon Krohn to discuss the future of machine learning within streaming data processing and reactive data processing. It’s another insight-packed episode you won’t want to miss! 1
/r/superdatascience, 2023-04-11, 11:47:18
Vin Vashishta speaks to host Jon Krohn about how to leverage GPT-4 and outperform your competitors in both speed and value. Learn how GPT-4 has outmatched its predecessors – and many skilled workers – in this latest iteration of large language models. 1
/r/superdatascience, 2023-04-04, 12:56:37
Is Meta AI's CICERO the greatest achievement in AI so far? Jon Krohn talks to Alexander Holden Miller about his work in building a machine that can outsmart humans in the game of Diplomacy by engineering powers of persuasion and collusion to its own advantage. 1
/r/superdatascience, 2023-03-21, 16:02:01
Superstar Chip Huyen graces the podcast this week to share her top tips for designing production-ready ML apps and the importance of iteration in getting them into the real world. And she and Jon Krohn share a few laughs too... Trust us – you won't want to miss this jam-packed episode! Tune in now 1
/r/superdatascience, 2023-03-14, 16:04:26
Learn to Predict User Sentiment from Text Comments | Data Science Masterclass 1
/r/superdatascience, 2023-03-14, 05:08:10
Annotation, awareness of syntax, figuring out intent: An NLP project comprises several parts. Vincent Warmerdam joins Jon Krohn today to explain how to ensure it is a success! 1
/r/superdatascience, 2023-03-07, 13:53:44
Your 1-hour data engineering primer has landed. This week, Andreas Kretz joins Jon Krohn to cover all things data engineering – the most in-demand and versatile role in data right now. Tune in if you're ready to future-proof your career. 1
/r/superdatascience, 2023-02-28, 14:13:48
Feeling siloed? Pandata’s Data Scientist in Residence Keith McCormick talks to host Jon Krohn about how data scientists can stop being treated like the company help desk. 1
/r/superdatascience, 2023-02-21, 14:11:13
Want to know how Glean founder and CEO, Carlos Aguilar, started and grew his data visualization startup? He joins Jon Krohn this week for an in-depth talk that covers topics like his software stack, founding team essentials and tips for keeping early adopters satisfied. 1
/r/superdatascience, 2023-02-14, 15:58:49
Coursera project 1

/r/superdatascience, 2023-02-13, 22:29:22
If color is the last thing you think about in your data visualizations, today’s guest Kate Strachnyi is about to tell you why you should rethink your priorities. Make intentional color choices for all your visualizations with Kate's tips. 1
/r/superdatascience, 2023-02-07, 15:54:28
How does AI influence human behavior and company culture? Tom Davenport speaks with Jon Krohn about the organizational obstacles to adopting AI, and why the C-suite also needs to learn how to handle data. 1
/r/superdatascience, 2023-01-24, 15:54:29
Do you want to understand how an end-2-end paraphrase app can be created? 1

/r/superdatascience, 2023-01-14, 15:46:41
Our data science predictions for 2023 are in! Sadie St. Lawrence joins Jon Krohn this week to share the top trends that we'll see dominate in the next 12 months. Are you ready? 1
/r/superdatascience, 2023-01-03, 16:00:11
Is AutoML the Swiss Army Knife of data science? Find out on this week’s episode of SuperDataScience, where Jon Krohn speaks with Erin LeDell, Chief Machine Learning Scientist at H2O.ai. 1
/r/superdatascience, 2022-11-15, 16:15:48
How can we improve betting in sports through data science? Jon Krohn asks this week’s guest Shashank Kalanithi about how he got started producing YouTube videos about data science, the essential differences between data science roles, and how the field could shape the future of the sports industry. 1
/r/superdatascience, 2022-11-01, 14:06:50
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/r/superdatascience, 2023-03-01, 03:29:47 , 1 score

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/r/superdatascience, 2020-05-29, 01:43:50 , 1 score

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/r/superdatascience, 2020-04-01, 11:28:59 , 1 score , -0.08 sentiment rating

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/r/superdatascience, 2020-03-30, 11:43:21 , 1 score , -0.45 sentiment rating

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/r/superdatascience, 2020-01-13, 17:20:22 , 1 score , +0.96 sentiment rating

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/r/superdatascience, 2019-12-25, 02:38:21 , 2 score

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/r/superdatascience, 2019-01-23, 05:17:46 , 1 score , +0.44 sentiment rating

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/r/superdatascience, 2018-10-06, 09:02:30 , 1 score , +0.85 sentiment rating

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/r/superdatascience, 2018-09-21, 11:59:02 , 2 score , +0.80 sentiment rating

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/r/superdatascience, 2018-08-20, 19:18:02 , 2 score

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/r/superdatascience, 2018-07-17, 19:58:26 , 1 score , +0.60 sentiment rating

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curl "https://socialgrep.com/api/v1/search/posts?query=%2Fr%2Fsuperdatascience" -H "Accept: application/json" -H "Authorization: Bearer YOUR_KEY"
Comments:
curl "https://socialgrep.com/api/v1/search/comments?query=%2Fr%2Fsuperdatascience" -H "Accept: application/json" -H "Authorization: Bearer YOUR_KEY"
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Query breakdown by source domain

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Query breakdown by subreddit posts

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Posts:
curl "https://socialgrep.com/api/v1/search/posts?query=%2Fr%2Fsuperdatascience" -H "Accept: application/json" -H "Authorization: Bearer YOUR_KEY"
Comments:
curl "https://socialgrep.com/api/v1/search/comments?query=%2Fr%2Fsuperdatascience" -H "Accept: application/json" -H "Authorization: Bearer YOUR_KEY"
For more information, see the API Reference page.

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