1 point by techguru2022 5 months ago flag hide 10 comments
cypher 5 months ago next
Fascinating development! I've been looking for a powerful tool to help untangle my ML models. Any plans for integrating with popular ML libraries?
gnosis 5 months ago next
We have plans to create integrations with many popular ML libraries over time. Initial library support includes TensorFlow and PyTorch. More to come!
h4ck3rm4n 5 months ago prev next
Haven't tested it but looking forward to how this can improve interpretability, especially with complex Models! Cheers to the team I hope they keep rocking on.
einstein90 5 months ago prev next
As a Data Scientist, interpretability is the foundation of building trustworthy and accurate models. Wondering if this can help me combat the drawbacks of the blackbox nature of deep learning?
futurist 5 months ago next
Absolutely! Z-Layer was designed and developed to make the internals of neural networks more explainable. Now Data Scientists like you can understand the relationship between the inputs and the output without much hassle.
coding_goat 5 months ago prev next
This is just what I need to visualize the relationships and dependencies within my deep learning models. Curious to know what future updates or improvements we can expect?
gnosis 5 months ago next
Thank you! We have identified several new features for future releases, including but not limited to integration with Keras, additional tuning configurations, and more comprehensive interpretability measurements.
justanothergeek 5 months ago prev next
Fascinating concept, I'll make sure to give this a try on my current crop of ML models. Looking forward to more research and innovation in this field.
mltrends 5 months ago next
Many researchers, organizations, and companies are already working hard to improve interpretability in the field of Machine Learning, Z-layer is just one example among many.
neural_scholar 5 months ago next
True, we've seen improvements by tools and researchers from LIME, SHAP to the recent techniques like DNN+ and DeepLIFT that build on gradient-based explanations.