Daniel Schafer

Enterprise Sales at Conversight

[Daniel Schafer @dhschafer]

Check out my latest article: Navigating NLP Adoption Challenges: From Hype to ROI https://t.co/CmFGgULeuX via @LinkedIn

[Daniel Schafer @dhschafer]

Check out my latest article: ChatGPT and Business Data: A Complex Dance of Possibilities and Pitfalls https://t.co/Ohzxc4PIzU via @LinkedIn

[Daniel Schafer @dhschafer]

https://t.co/Ur4dNWRT4T

[Daniel Schafer @dhschafer]

https://t.co/gXAgYfJ7y8

[Daniel Schafer @dhschafer]

Don't just take our word for it… DataRobot customers have spoken and named us Customers' Choice 2021in Gartner Peer Insights: 'Voice of the Customer': Data Science and Machine Learning (ML) Platforms. The Best In Class MLOps Vendor. https://t.co/JYCephoEcN

[Daniel Schafer @dhschafer]

Good explanation on the Value of MLOps for the enterprise #mlops #datarobot
https://t.co/J2IOwhJDkJ

[Daniel Schafer @dhschafer]

Using MLOps to make sense out of Big Data #mlops #datarobot
https://t.co/IHU9ZO0nIe

[Daniel Schafer @dhschafer]

Common Mistakes and Pitfalls with MLOps #mlops #algorithmia
https://t.co/Fi0BFXJpqh

[Daniel Schafer @dhschafer]

MLOPs market to grow to $4B by 2025. Productionization for Machine Learning is still early for most of companies. #mlops #algorithmia
https://t.co/BJko3tGxiZ

[Daniel Schafer @dhschafer]

Great Example on how to solve MLOps challenges if you have the talent and time...#algorithmia #mlops
https://t.co/kb50t0qEmB

[Daniel Schafer @dhschafer]

Algorithmia makes the List for the hottest AI startup Companies in 2021! #mlops #algorithmia
https://t.co/TI3zRQrj9Q

[Daniel Schafer @dhschafer]

Great Conversation on the importance of Security and a ML Threat Model for ML Systems before production deployment #mlops #algorithmia
https://t.co/KD7YsSKpy2

[Daniel Schafer @dhschafer]

Raytheon Selected Algorithmia to help support Army's Tactical Intelligence. #algorithmia #mlops
https://t.co/AJ8toT4EBS

[Daniel Schafer @dhschafer]

MLOps enable you to realize ML use cases that see triple digit lift in click through rates. #mlops @algorithmia
https://t.co/2ZNX3Wu2Yu

[Daniel Schafer @dhschafer]

MLOps combines the resources needed to train and deploy into continuous production ML algorithms within a business context. #algorithmia #mlops
https://t.co/SzcoqMIT5H

[Daniel Schafer @dhschafer]

Model Governance is a key feature in MLOps #algorithmia #mlops
https://t.co/0teV7NmmWL

[Daniel Schafer @dhschafer]

MLOps is the last Mile that will help you realize your ML Model development investment #mlops #algorithmia
https://t.co/1Jdtf4vbAH

[Daniel Schafer @dhschafer]

Using MLOps to speed up drug discovery #algorithmia #mlops
https://t.co/batosk5CDE

[Daniel Schafer @dhschafer]

Great article on articulating the complexity of productionizing ML models #mlops #algorithmia
https://t.co/hfTIVRP6xb

[Diego Oppenheimer @doppenhe]

Operational ML is about automation. New feature to continue pushing the boundaries of ML in production at scale.