- KDD-2021, The premier Data Science Conference, Aug 14-18, Virtual, by KDD 2021 - Apr 27, 2021.
KDD 2021, the Association for Computing Machinery (ACM) Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) flagship conference, will take place virtually Aug 14-18.
- Learn how to integrate third-party location data with AWS Data Exchange, by AWS - Apr 26, 2021.
Join this webinar, May 6 @ 2PM ET, to discover how Yum! Brands and other organizations are leveraging location-based data to boost in-app location accuracy, increase in-store foot traffic, and expand ecommerce business.
- The Three Edge Case Culprits: Bias, Variance, and Unpredictability, by iMerit - Apr 22, 2021.
Edge cases occur for three basic reasons: Bias – the ML system is too ‘simple’; Variance – the ML system is too ‘inexperienced’; Unpredictability – the ML system operates in an environment full of surprises. How do we recognize these edge cases situations, and what can we do about them?
- How Uber manages Machine Learning Experiments with Comet.ml, by Comet.ml - Apr 21, 2021.
At Uber, where ML is fundamental to most products, a mechanism to manage offline experiments easily is needed to improve developer velocity. To solve for this, Uber AI was looking for a solution that will potentially complement and extend its in-house experiment management and collaboration capabilities.
- Top 10 Data Science Courses to Take in 2021, by Coursera - Apr 20, 2021.
Whether you are getting started with Data Science / Machine Learning or are an experienced professional looking to learn something new, check out these top 10 data science courses for 2021.
- Knowledge Graph Conference, covering tools, techniques, case studies and more, by experts. May 3-6, Virtual, by Knowledge Graph Conference - Apr 19, 2021.
"A force to be reckoned with" - the who’s who of knowledge graphs will convene at The Knowledge Graph Conference in May.
- 6 Mistakes To Avoid While Training Your Machine Learning Model, by Cogito Tech - Apr 15, 2021.
While training the AI model, multi-stage activities are performed to utilize the training data in the best manner, so that outcomes are satisfying. So, here are the 6 common mistakes you need to understand to make sure your AI model is successful.
- Shaping the new digital age – with SAS and Microsoft, by SAS - Apr 13, 2021.
Join technology experts, partners and analysts in the industry for this webinar series to see how SAS Viya can help you make the most of AI, analytics and the cloud for faster decisions and trusted results.
- Can Robots and Humans Combat Extinction Together? Find Out April 17, by DataYap - Apr 8, 2021.
Get ready to trade that “Zoom fatigue” for Zoom euphoria at the DataYap Virtual Conference, Apr 17, where you’ll have your pick of 15 panels on some of the hottest topics in the data and technology space led by some of the top names in data science.
- Start a Career in a Growing Field with Google’s Data Analytics Professional Certificate, by Coursera - Apr 7, 2021.
Google's recently launched Data Analytics Professional Certificate on Coursera is great for anyone, regardless of background or experience. The program is completely online, self-paced, and costs $39 per month. Interested in preparing for a new career in a high-growth field?
- How Noisy Labels Impact Machine Learning Models, by iMerit - Apr 6, 2021.
Not all training data labeling errors have the same impact on the performance of the Machine Learning system. The structure of the labeling errors make a difference. Read iMerit’s latest blog to learn how to minimize the impact of labeling errors.